System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving problem data input by a user; means for sending the problem data to a generative model for analysis and verbalization; means for storing the verbalized problem data in a database; means for generating and publishing the stored problem data for display; means for accepting empathy and funding for the published problem data; means for receiving and storing the empathy and funding data; and means for generating, publishing, and notifying problem-solving progress information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern society, diversifying values ​​and lifestyles are giving rise to a variety of social issues that deviate from conventional norms. It often takes time for appropriate terms to be developed and recognized for these issues, such as maternity harassment, and many people suffer in the meantime.

[0005] Conventional systems and methods lack the means to quickly and appropriately verbalize the problems and suffering felt by individuals, and to widely acknowledge and garner sympathy for them. Furthermore, there are insufficient concrete mechanisms in place to quickly resolve social issues at the local or individual level, rather than through government leadership. This has made it difficult to quickly respond to and promote solutions to the increasing number of social issues caused by the diversification of values.

[0006] The purpose of this invention is to promote the rapid resolution of social issues by communities and individuals by using generative models to verbalize social issues and solicit sympathy and investment for them. [Means for solving the problem]

[0007] The present invention is a system that includes a means for receiving problem data entered by a user, a means for sending the problem data to a generative model and analyzing and verbalizing it, a means for saving the verbalized problem data in a database, a means for generating and publishing the saved problem data for display, a means for accepting sympathy and contributions for the published problem data, a means for receiving and saving the sympathy and contribution data, and a means for generating, publishing, and notifying problem-solving progress information.

[0008] Specifically, it includes a means to convert the problem data entered by the user into JSON format and send it via HTTPS protocol, a means to convert the verbalized data returned by the generative model into an appropriate format, a means to periodically update the progress of the problem solution and notify the investors by email, and a means for users to check the progress using a dedicated dashboard.

[0009] In this way, the present invention promotes the appropriate articulation of social issues, the rapid expansion of awareness and empathy, and the resolution of these issues at the local and individual levels through investment.

[0010] "Users" refer to ordinary users who use the system to input social issues, or who sympathize with or invest in published issues.

[0011] A "terminal" is a device used by a user, specifically including a smartphone, PC, tablet, etc., and refers to equipment for inputting and outputting data to the system.

[0012] "Server" refers to the central computer system that receives, processes, and stores data from terminals, calls the API of the generative model, and manages tasks, such as publishing and investment information.

[0013] "Issue data" refers to text data entered by users that expresses social issues or personal suffering.

[0014] A "generative model" is specifically a language generation model that uses artificial intelligence, and refers to a technology for verbalizing task data into appropriate words.

[0015] "Verbalized data" refers to task data that has been analyzed by a generative model and converted into concrete words and formats.

[0016] "Database" refers to storage within a system for storing and managing verbalized data, empathy data, investment data, etc.

[0017] "Sympathy data" refers to data generated by users' input or clicks to express their sympathy for a published issue.

[0018] "Investment data" refers to information about resources (time, money, skills, etc.) that users provide as support for published challenges.

[0019] "Progress information" refers to data that is regularly updated to show the activities and results achieved in solving a problem.

[0020] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, and refers to a standard format for expressing data in a format that is easy for humans to read and for exchanging data between systems.

[0021] "HTTPS protocol" is an abbreviation for Hypertext Transfer Protocol Secure, and refers to a communication protocol for securely sending and receiving data.

[0022] "Publication means" refers to a mechanism for displaying verbalized assignment data on a web page or app, making it viewable by many users.

[0023] "Means for accepting sympathy and investment" refers to a function that enables the system to receive sympathy and investment intentions from users.

[0024] A "dashboard" refers to an interface that allows users to visually check the progress of projects in which they have invested or sympathized. [Brief explanation of the drawings]

[0025] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0026] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0027] First, the terms used in the following description will be explained.

[0028] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0029] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0030] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0031] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0032] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0033] [First embodiment]

[0034] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0035] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0036] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0037] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0038] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0039] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0040] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0041] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0042] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0043] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0044] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0045] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0046] This invention is a system that aims to quickly verbalize the social issues and personal suffering that users are facing, and to widely solicit sympathy and investment. This system is based on cooperation between a server, a terminal, and a user, and is characterized by its ability to appropriately verbalize issues using a generative model.

[0047] System Overview

[0048] 1. User Input

[0049] Users access the system using a device (smartphone or PC). A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. Here, users enter text about the social issues and personal suffering they are facing. Once they have finished entering the text, they press the send button.

[0050] 2. Sending and Receiving Input Data

[0051] The terminal receives the data entered by the user, converts it to JSON format, and then sends the converted data using the HTTPS protocol to the server, which receives the data and prepares it for analysis.

[0052] 3. Data analysis and verbalization

[0053] The server passes the received JSON data to a generative model (such as ChatGPT (registered trademark)), which analyzes and verbalizes the data. The generative model then organizes the problem data into appropriate terms and converts it into specific social issues. For example, if the content includes "I am being harassed at work because I am pregnant," this can be verbalized as "An example of maternity harassment is being excluded from promotions or jobs at work because of pregnancy."

[0054] 4. Preservation and publication of verbalized data

[0055] The server stores the verbalized data returned by the generative model in a database, which then converts it into a publicly available format and displays it on a dedicated web page or application, allowing other users to access and view this information.

[0056] 5. Seeking sympathy and investment

[0057] Other users can sympathize with the published challenge. By clicking the "Sympathize" button, users can send their feedback to the system. If users want to contribute their resources (time, money, skills, etc.) to the challenge, they can click the "Contribute" button and fill in the appropriate form.

[0058] 6. Management of investment information

[0059] The terminal sends the user's contribution information to the server. The server receives this information and stores it in a database. Once the contribution information is registered, a thank-you message is sent to the user.

[0060] 7. Progress Feedback

[0061] The server periodically updates the progress of the problem-solving process and displays it on a special webpage and application. Users who have invested or sympathized with the project will be notified of the progress by email. A dedicated dashboard will also be provided, allowing users to check detailed progress information in real time.

[0062] Specific examples

[0063] User A inputs and submits "an experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server then sends the received data to a generative model, which verbalizes it specifically as "maternity harassment, a case where a woman is excluded from promotions or work because of pregnancy." The verbalized data is saved in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is saved on the server, and the progress of problem-solving is regularly updated.

[0064] The above is a specific description of an embodiment of the present invention. This system allows for quick verbalization and recognition of issues, and promotes investment and solutions by communities and individuals.

[0065] The processing flow will be explained below.

[0066] Step 1:

[0067] A user logs in to the system's web page or application using a device (smartphone or PC).

[0068] Step 2:

[0069] Users click the "Post a new social issue" button to access a new entry form, where they can enter the social issues or personal suffering they are facing in the text area.

[0070] Step 3:

[0071] When the user completes the input, they press the "Submit" button, which converts the input data into JSON format data on the device.

[0072] Step 4:

[0073] The device sends this JSON format data to the server using the HTTPS protocol, after which a message indicating successful data transmission is displayed to the user.

[0074] Step 5:

[0075] The server analyzes the received JSON data and extracts necessary fields (user ID, details of the social issue, etc.), and prepares the extracted data for passing to the generative model.

[0076] Step 6:

[0077] The server calls the API of the generative model (such as ChatGPT) and sends the analyzed data. Based on the received data, the generative model verbalizes the social issues in appropriate terms.

[0078] Step 7:

[0079] The generative model returns the verbalized data to the server, for example, "Pregnant employees are harassed at work and excluded from promotions and jobs."

[0080] Step 8:

[0081] The server receives the verbalized data and stores it in the database, logging the success of the save.

[0082] Step 9:

[0083] The server then formats the stored data for public viewing and displays it on a special web page or application, making the information accessible to other users.

[0084] Step 10:

[0085] Users can click the "Sympathize" button for a published issue, or if they want to enter a comment or provide specific support, they can click the "Invest" button and enter the required information.

[0086] Step 11:

[0087] The device converts data related to sympathy and investment into JSON format and sends it back to the server via HTTPS protocol.

[0088] Step 12:

[0089] The server receives the empathy data and the contribution data and stores them in a database. Once the contribution information is saved, a thank you message is sent to the user.

[0090] Step 13:

[0091] The server periodically updates the progress of the problem and displays it on a web page or application, allowing users to check the progress.

[0092] Step 14:

[0093] Users can use a dedicated dashboard to check the progress and new information on the projects they have funded in real time.

[0094] Step 15:

[0095] The server periodically notifies the contributor of the progress by email. This notification is sent automatically according to the timing of updates to the progress status within the system.

[0096] This is the specific processing flow of this system, which enables appropriate verbalization and rapid recognition of social issues, as well as promoting investment and solutions by communities and individuals.

[0097] Example 1

[0098] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0099] In conventional systems, it was difficult for users to quickly and appropriately verbalize the personal or social challenges they faced and to solicit sympathy and investment from other users. In addition, there was a lack of visualization of the progress of the challenges and information provided to investors, making it difficult to provide support for problem-solving efficiently.

[0100] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0101] In this invention, the server includes a means for receiving task data entered by a user, a means for converting the task data into JSON format, and a means for transmitting the converted JSON format data via HTTPS, thereby enabling the task data entered by a user to be quickly and appropriately transmitted to the server for analysis and verbalization.

[0102] "User" refers to an individual or corporation that uses this system to input issue data and sympathize with or invest in the project.

[0103] "Issue data" refers to information entered in text format about social issues or personal problems that users are facing.

[0104] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight text data format that represents data in a structured manner.

[0105] "HTTPS protocol" stands for HyperText Transfer Protocol Secure and refers to an internet protocol for secure communication.

[0106] A "generative AI model" refers to an artificial intelligence model that uses natural language processing to analyze input data and convert it into an appropriate language.

[0107] A "database" refers to a system for organizing and storing information, and for efficiently searching, retrieving, and updating information as needed.

[0108] "Publication format" refers to a format in which data has been converted into a form that can be viewed by other users, such as HTML or JSON.

[0109] "Empathy" refers to the act of users expressing emotional reactions to published assignment data and sending feedback.

[0110] "Investment" refers to the act of a user providing their own resources (time, money, skills, etc.) to solve a problem.

[0111] A "staging area" refers to an area where received data is temporarily stored and its format and content are validated.

[0112] "Validation" refers to the process of checking whether the content of data is accurate and valid.

[0113] "Dedicated form" refers to a special input screen provided within the system for users to input assignment data.

[0114] The "thank you message" refers to a message sent from the server to the user who made the investment, expressing gratitude.

[0115] A "dashboard" refers to a visual interface that allows users to check the progress of problem-solving in real time.

[0116] A "scheduler" refers to a program that executes a specific process at a fixed time.

[0117] This invention is a system that operates in cooperation with the user, the terminal, and the server. Specifically, it quickly analyzes the problem data entered by the user, properly verbalizes it, and then publishes it, thereby streamlining the process of soliciting sympathy and investment.

[0118] System Configuration

[0119] User Input

[0120] Users access the system using a device (smartphone or PC). They can enter the social issues and personal suffering they are facing in text format through a dedicated web page or application. This input is saved at regular intervals using an auto-save function. After completing the input, the user clicks the send button, and the data is converted into JSON format and sent to the server using the HTTPS protocol.

[0121] Sending and Receiving Data

[0122] The terminal converts the data entered by the user into JSON format and sends it to the server via the HTTPS protocol. The server temporarily stores the received data in a staging area and validates the data to ensure that its format and content are appropriate.

[0123] Data analysis and verbalization

[0124] The server formats the JSON data stored in the staging area so that it can be used by a generative AI model (e.g., ChatGPT). This formatted data is passed to the generative model, which analyzes the data and verbalizes the problem. For example, if an input is "I am being harassed at work because I am pregnant," the generative model verbalizes this as "An example of maternity harassment is being excluded from promotions or work because of pregnancy."

[0125] Storing and publishing verbalized data

[0126] The server stores the verbalized data returned by the generative model in a database. This stored data can then be converted into a publicly available format (e.g., HTML or JSON) and displayed on a dedicated web page or application. This process allows other users to access and view this information.

[0127] Seeking sympathy and investment

[0128] Other users can express their "sympathy" for the published challenge. Users who want to express their sympathy click the "Sympathy" button, and their feedback is sent from their device to the server. Users can also click the "Invest" button and enter details of their resources, such as time, money, or skills, into a dedicated form. This information is also sent from their device to the server.

[0129] Management of investment information

[0130] The terminal converts the user's contribution information into JSON format and sends it to the server via HTTPS. After receiving the contribution information, the server validates it and stores it in the database. After the contribution is completed, a thank-you message is sent to the user.

[0131] Progress feedback

[0132] The server periodically updates the progress of the problem-solving process. This progress information is retrieved from the database and displayed on a dedicated web page or application. Users who have contributed or sympathized with the project are also notified of the progress via email. A system is also provided that allows users to check progress information in real time via a dedicated dashboard.

[0133] Prompt Sentence Examples

[0134] Please explain in detail the harassment you have experienced in the workplace.

[0135] The above is a specific embodiment of the present invention, which enables a user to quickly and appropriately verbalize the issues they face and solicit sympathy and investment from other users.

[0136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0137] Step 1:

[0138] Users log in to the system using their own device (smartphone or PC). They enter the social issues and personal suffering they are facing in text format into a dedicated form. The input information is automatically saved at regular intervals. Once the input is complete, the user clicks the send button.

[0139] Input: User-entered assignment data (text format)

[0140] Output: Send instructions are generated on the user's terminal

[0141] Step 2:

[0142] The terminal receives the task data entered by the user, converts it into JSON format, and sends the converted data to the server using the HTTPS protocol.

[0143] Input: User-entered assignment data (text format)

[0144] Data processing: Converting issue data into JSON format

[0145] Output: JSON format data is sent to the server

[0146] Step 3:

[0147] The server temporarily stores the JSON data received via HTTPS in a staging area, where the format and content of the data are validated.

[0148] Input: Issue data in JSON format

[0149] Data processing: Validating the format and content of JSON data

[0150] Output: Pass validated JSON data to the generated AI model

[0151] Step 4:

[0152] The server passes the validated JSON data to a generative AI model (e.g., ChatGPT), which analyzes and verbalizes the data. The generative model then organizes the input data into appropriate terms and converts them into specific social issues. For example, if an input states, "I am being harassed at work because I am pregnant," the generative model verbalizes this as, "An example of maternity harassment is being excluded from promotions or jobs at work because of pregnancy."

[0153] Input: Validated JSON data

[0154] Data Computation: Data Analysis and Verbalization with Generative AI Models

[0155] Output: Verbalized task data

[0156] Step 5:

[0157] The server stores the verbalized data returned by the generative AI model in a database, converts the stored data into a publicly available format (e.g., HTML, JSON), and displays it on a dedicated webpage or application.

[0158] Input: Verbalized task data

[0159] Data processing: converting data into a format for publication

[0160] Output: Data displayed on a dedicated web page or application

[0161] Step 6:

[0162] Other users can express their sympathy for the published problem data. By clicking the "Sympathize" button, feedback is sent from the device to the server. Users can also click the "Invest" button and enter details of their resources, such as time, money, or skills, into a dedicated form. This information is also sent from the device to the server.

[0163] Input: The like or pledge button the user clicked

[0164] Data processing: Sending feedback or contribution information

[0165] Output: Empathy or pledge data sent to the server

[0166] Step 7:

[0167] The server receives the sympathy and contribution data, validates the contents, and stores them in the database. After the contribution is completed, a thank you message is sent to the user.

[0168] Input: Empathy data, investment data

[0169] Data processing: validation and saving to database

[0170] Output: Validated empathy data, pledge data, and a thank you message

[0171] Step 8:

[0172] The server periodically updates the progress of the project. This progress information is retrieved from the database and displayed on a dedicated web page or application. Users who have contributed or sympathized are notified of the progress by email, and can check the progress information in real time through a dedicated dashboard.

[0173] Input: Progress information in the database

[0174] Data processing: Updating and obtaining progress information

[0175] Output: Publishing and notifying progress updates

[0176] (Application example 1)

[0177] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0178] Conventional problem-solving systems lacked sufficient means for users to quickly verbalize the social issues and personal suffering they faced and then share that information widely. Furthermore, they lacked a means to create advertisements based on verbalized problem data and efficiently solicit sympathy and investment, making it difficult to effectively gather support for problem-solving. For this reason, a new system was needed to quickly and effectively solve users' problems across society.

[0179] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0180] In this invention, the server includes means for transmitting problem data entered by the user to a generative model for analysis and verbalization, means for embedding the generated verbalized data in an advertising template to generate an advertisement, and means for distributing the generated advertisement to social media and websites. This makes it possible to quickly share users' problems and generate advertisements based on them to effectively attract sympathy and investment.

[0181] A "user" is an individual or organization that inputs assignment data and shares that assignment through the system.

[0182] "Issue data" is text data that expresses the social issues and personal suffering that users are facing.

[0183] A "generative model" is an artificial intelligence model that analyzes input task data and converts it into appropriate words.

[0184] "Verbalized data" is task data that has been analyzed by a generative model and converted into an appropriate format.

[0185] An "advertising template" is a model of an advertisement prepared for embedding generated verbalized data.

[0186] "Advertising" refers to content generated based on verbalized data and distributed on social media and websites.

[0187] "Social media" is a general term for online platforms through which users receive advertising.

[0188] A "Website" is an online page for displaying advertisements on the Internet.

[0189] "Empathy" is an act in which other users show emotional understanding and support for a published issue.

[0190] "Contribution" is the act of a user providing resources such as time, money, or skills to a published challenge.

[0191] "Progress information" is data that indicates the progress of problem solving and the current situation.

[0192] "Advertising status management" is the process of monitoring and controlling the status of advertising on social media and websites.

[0193] This invention is a system that allows users to quickly verbalize social issues and personal suffering they are facing and share that information widely. This system aims to effectively attract sympathy and investment by creating advertisements based on the generated verbalization data through collaboration between users, devices, generative models, and servers.

[0194] System Overview

[0195] 1. User input:

[0196] Users access the system using devices such as smartphones or PCs. A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. The text entered in this form is treated as assignment data.

[0197] 2. Receiving and sending assignment data:

[0198] The terminal receives the assignment data entered by the user, converts it into JSON format, and then sends the converted data to the server using the HTTPS protocol.

[0199] 3. Data analysis and verbalization:

[0200] The server passes the received JSON data to a generative model (such as ChatGPT) to analyze and verbalize the data. The generative model then organizes and converts the problem data into appropriate language, converting it into specific social issues.

[0201] 4. Ad generation and delivery:

[0202] The server embeds the generated verbalized data into an advertising template, which generates an advertisement designed to resonate with users. The generated advertisement is then distributed to social media and websites. The server also collects and analyzes user feedback on the advertisement to evaluate its effectiveness.

[0203] 5. Empathy and stake management:

[0204] Other users can express their sympathy for the published issues. Data on sympathy and contributions is also sent to the server and stored in a database. The server periodically updates the progress of the issue and notifies the contributors and other stakeholders by email.

[0205] Specific examples

[0206] For example, User A inputs her experience of "being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server then sends this data to a generative model, which verbalizes it specifically as "problems related to maternity harassment in the workplace." The verbalized data is embedded in an ad template, and an ad is automatically generated that reads, "(Relatable ad) Problem: Maternity harassment is occurring in the workplace. We need your support. Learn more: www.example.com / donate." This ad is then distributed on social media and websites, and feedback is collected.

[0207] Prompt Sentence Examples

[0208] An example of an input prompt for a generative AI model is as follows:

[0209] "Verbalize the following user input for advertising: I am being harassed at work because I am pregnant"

[0210] The above description provides a detailed explanation of how the present invention can be implemented, allowing users to quickly articulate the challenges they face and gain widespread sympathy and investment.

[0211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0212] Step 1:

[0213] Users access a dedicated web page or application using a device such as a smartphone or PC and input their experiences and thoughts. The input data is treated as assignment data. In this case, the text data entered by the user becomes input data to be passed on to the next processing step.

[0214] Step 2:

[0215] The terminal receives the assignment data entered by the user and converts it into JSON format. The converted data is sent to the server using the HTTPS protocol. Here, the input is the assignment data and the output is JSON format data.

[0216] Step 3:

[0217] The server passes the received JSON data to a generative model, which analyzes and verbalizes the data. The generative model (such as ChatGPT) organizes and converts the task data into appropriate language. The input for this process is JSON data, and the output is verbalized data. Specific data processing involves analyzing the task data and converting it into appropriate language expressions.

[0218] Step 4:

[0219] The server embeds the generated verbalized data into an advertising template. The advertising template is a pre-prepared format, and specific advertising content is generated by embedding the verbalized data. The inputs to this process are the verbalized data and the advertising template, and the output is the generated advertisement. Specifically, the verbalized data is inserted into a placeholder in the template.

[0220] Step 5:

[0221] The server distributes the generated advertisements to social media platforms and websites. After the advertisements are distributed, users can provide feedback on the advertisements. The input of this process is the generated advertisement, and the output is the distributed advertisement and user feedback. Specifically, the advertisements are sent to social media APIs and the website's advertisement management system.

[0222] Step 6:

[0223] The server collects and analyzes user responses to advertisements from social media and websites. The effectiveness of the advertisements is evaluated based on the collected feedback data. The input to this process is the feedback data, and the output is the analysis results. Specifically, the feedback data is stored in a database and statistical analysis and text mining are performed.

[0224] Step 7:

[0225] Other users can express their support or investment in the published issues. The server also receives this data and stores it in a database. Based on the support and investment data, progress information on the issue resolution is generated, updated periodically, and notified to investors and related parties via email. The input to this process is support and investment data, and the output is progress information and notification emails. Specifically, the support and investment data is analyzed, progress information is generated, and notifications are sent using the email system.

[0226] The above are the specific processing steps of the program for the system that realizes the application example.

[0227] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0228] This invention is a system that aims to quickly verbalize the social issues and personal suffering faced by users, and to widely solicit sympathy and investment. This system is based on collaboration between a server, a device, and a user, and is characterized by its ability to appropriately verbalize issues using a generative model. In addition, by combining it with an emotion engine that recognizes the user's emotions, it enables more accurate analysis and more effective motivation for sympathy and investment.

[0229] System Overview

[0230] 1. User Input

[0231] Users access the system using a device (smartphone or PC). A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. Here, users enter text about the social issues and personal suffering they are facing. Once they have finished entering the text, they press the send button.

[0232] 2. Sending and Receiving Input Data

[0233] The terminal receives the data entered by the user, converts it to JSON format, and then sends the converted data using the HTTPS protocol to the server, which receives the data and prepares it for analysis.

[0234] 3. Emotion Data Recognition and Analysis

[0235] The server applies an emotion engine to the received JSON data to analyze the user's emotions. For example, it extracts emotions (happiness, sadness, anger, etc.) from the text data and generates an emotion score.

[0236] 4. Data analysis and verbalization

[0237] Taking the analyzed emotion data into consideration, the server passes the received JSON data to a generative model (such as ChatGPT) for data analysis and verbalization. The generative model then organizes the problem data into appropriate terms and converts it into a specific social issue. For example, a statement such as "A pregnant employee was harassed at work and excluded from promotions and work" can be verbalized as "An example of maternity harassment is being excluded from promotions and work due to pregnancy."

[0238] 5. Preservation and publication of verbalized data

[0239] The server stores the verbalized and emotional data returned by the generative model in a database, which then converts the data into a publicly available format and displays it on a dedicated web page or application, allowing other users to access and view the information.

[0240] 6. Seeking sympathy and investment

[0241] Other users can sympathize with the published challenge. By clicking the "Sympathize" button, users can send their feedback to the system. If users want to contribute their resources (time, money, skills, etc.) to the challenge, they can click the "Contribute" button and fill in the appropriate form.

[0242] 7. Management of investment information

[0243] The terminal sends the user's contribution information to the server. The server receives this information and stores it in a database. Once the contribution information is registered, a thank-you message is sent to the user.

[0244] 8. Progress Feedback

[0245] The server periodically updates the progress of the problem-solving process and displays it on a special webpage and application. Users who have invested or sympathized with the project will be notified of the progress by email. A dedicated dashboard will also be provided, allowing users to check detailed progress information in real time.

[0246] Specific examples

[0247] User A inputs and submits her "experience of workplace harassment due to pregnancy." This data is converted to JSON format and sent to the server via HTTPS protocol. The server analyzes the received data through an emotion engine and generates an emotion score. This is then sent to the generative model along with the analyzed emotion data, which is then specifically verbalized as "maternity harassment, a case where a woman is excluded from promotions or work due to pregnancy." The verbalized data and emotion data are stored in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is stored on the server, and the progress of problem-solving is regularly updated.

[0248] The above is a specific description of an embodiment of the present invention. This system enables quick verbalization and recognition of issues, and promotes investment and solutions by communities and individuals. Furthermore, by recognizing the user's emotions, it is possible to empathize more effectively and motivate investment.

[0249] The processing flow will be explained below.

[0250] Step 1:

[0251] A user logs in to the system's web page or application using a device (smartphone or PC).

[0252] Step 2:

[0253] The user clicks the "Post a new social issue" button to access a new entry form. Here, the user enters the social issue or personal suffering they are facing into the text area. For example, the user could provide details such as "I was harassed at work because I am pregnant."

[0254] Step 3:

[0255] When the user completes the input, they press the "Submit" button, which converts the input data into JSON format data on the device.

[0256] Step 4:

[0257] The device sends this JSON format data to the server using the HTTPS protocol, after which a message indicating successful data transmission is displayed to the user.

[0258] Step 5:

[0259] The server analyzes the received JSON data and extracts necessary fields (user ID, details of the social issue, etc.), and prepares the extracted data for passing to the generative model.

[0260] Step 6:

[0261] The server sends the task data to the emotion engine, which extracts emotions from the text data and generates an emotion score (e.g., ranging from 0 to 1 representing joy, sadness, anger, etc.).

[0262] Step 7:

[0263] The analyzed data, along with the emotion score generated by the server, is sent to a generative model (e.g., ChatGPT) for analysis and verbalization. The generative model then organizes the issue data into concrete terms and converts it into a social issue. For example, "I was harassed at work because I was pregnant" is verbalized as "An example of maternity harassment is when a woman is excluded from promotions or jobs at work because she is pregnant."

[0264] Step 8:

[0265] The server saves the verbalized data and sentiment scores returned by the generative model to a database, and logs the success of the save.

[0266] Step 9:

[0267] The server then formats the stored data for public viewing and displays it on a special web page or application, making the information accessible to other users.

[0268] Step 10:

[0269] Users can click the "Sympathize" button for a published issue, or if they want to enter a comment or provide specific support, they can click the "Invest" button and enter the required information.

[0270] Step 11:

[0271] The device converts data related to sympathy and investment into JSON format and sends it back to the server via HTTPS protocol.

[0272] Step 12:

[0273] The server receives the empathy data and the contribution data and stores them in a database. Once the contribution information is saved, a thank you message is sent to the user.

[0274] Step 13:

[0275] The server periodically updates the progress of the problem and displays it on a web page or application, allowing users to check the progress.

[0276] Step 14:

[0277] Users can use a dedicated dashboard to check the progress and new information on the projects they have funded in real time.

[0278] Step 15:

[0279] The server periodically notifies the contributor of the progress by email. This notification is sent automatically according to the timing of updates to the progress status within the system.

[0280] As a concrete example, User A inputs and submits "an experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server analyzes the received data using an emotion engine to generate an emotion score. This is then sent to the generative model along with the analyzed emotion data, which is specifically verbalized as "maternity harassment, a case where a woman is excluded from promotions or work because of pregnancy." The verbalized data and emotion data are stored in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and makes an additional investment of 1,000 yen. This information is stored on the server, and the progress of problem-solving is regularly updated.

[0281] The above is the specific processing flow of this system. This enables appropriate verbalization and rapid recognition of social issues, as well as promoting investment and solutions by communities and individuals. Furthermore, the introduction of an emotion engine enables analysis that takes into account the user's emotions and expands empathy.

[0282] Example 2

[0283] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0284] In modern society, there is a lack of ways for individuals to quickly verbalize the social issues and personal suffering they face and to solicit widespread sympathy and investment. As a result, individual problems are not easily recognized by society, and it takes a long time to receive effective support. Furthermore, the lack of a system that can appropriately handle users' emotions means that there is insufficient motivation for empathy and investment.

[0285] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0286] In this invention, the server includes means for receiving task data entered by a user, means for converting the received task data into JSON format, means for transmitting the converted data via HTTPS protocol, means for analyzing the task data and generating an emotional score, means for transmitting the analyzed emotional score and task data to a generative AI model for analysis and verbalization, means for saving the verbalized task data in a database, means for generating and publishing the saved task data for display, means for accepting sympathy and contributions for the published task data, means for receiving and saving the sympathy and contribution data, and means for generating, publishing, and notifying progress information on problem solving. This enables the task data to be quickly verbalized and widely shared, and motivates sympathy and contributions.

[0287] "User" refers to any individual or entity that uses the System.

[0288] "Issue data" refers to text data entered by users about social issues or personal suffering.

[0289] "JSON format" refers to a JavaScript Object Notation data structure, a text format used for exchanging and storing data.

[0290] The "HTTPS protocol" is a communication protocol for securely transferring data over the Internet.

[0291] "Emotion score" refers to a numerical representation of the type and intensity of emotions extracted from text data.

[0292] A "generative AI model" refers to an artificial intelligence algorithm that uses a large-scale language model to parse and verbalize data.

[0293] A "database" refers to a system for efficiently storing, managing, and searching large amounts of data.

[0294] "Publication" refers to making the stored data publicly available for viewing via the Internet.

[0295] "Empathy" refers to the act of other users showing sympathy or understanding for a published issue.

[0296] "Contribution" refers to the act of other users providing resources (funds, time, skills, etc.) to a published challenge.

[0297] "Thank you message" refers to a message of gratitude sent from the server when a user makes a contribution.

[0298] "Progress information" refers to data regarding the progress of activities toward resolving a problem.

[0299] A "dashboard" refers to an interface designed to allow users to see the status and progress of a system at a glance.

[0300] This invention is a system that aims to quickly verbalize the social issues and personal suffering faced by users, and to widely solicit sympathy and investment. The system is based on three-way collaboration between a server, a terminal, and a user. This enables the appropriate verbalization of issues using a generative AI model, combined with an emotion engine that recognizes the user's emotions, enabling more accurate analysis and effective motivation for sympathy and investment. The specific hardware and software used will be explained in turn.

[0301] First, the user accesses the system using a terminal. The terminal can be a smartphone or personal computer, and a form is provided for the user to enter their experiences and thoughts. The user enters the assignment data through a dedicated web page or application and presses the submit button.

[0302] The device receives text data entered by the user and converts it to JSON format. It then sends it to the server using the HTTPS protocol. The server prepares the received JSON data for analysis. Specifically, the server uses an emotion engine (e.g., IBM Watson® or Google® Cloud Natural Language API) to analyze the user's emotions. This process extracts emotions such as joy, sadness, and anger from the entered text data and generates an emotion score.

[0303] The server then passes the analyzed emotion data and issue data to a generative AI model (such as ChatGPT). The generative AI model then organizes the given issue data into appropriate language and converts it into a specific social issue. For example, a statement such as "A pregnant employee was harassed at work and excluded from promotions and work" can be verbalized as "Maternity harassment involves being excluded from promotions and work due to pregnancy."

[0304] The server stores the verbalized data in a database, converts the data into a public format, and instantly publishes it on a special web page or application, allowing other users to view the information.

[0305] Other users can show their support or investment in the published challenge. By clicking the "Support" button, users can send feedback to the system. Also, by clicking the "Invest" button, users who want to donate their resources (time, money, skills, etc.) can fill out the appropriate form and send it from their device to the server. The server stores the received investment information in a database and manages it.

[0306] Furthermore, the server periodically updates the progress of the project and displays it on a special webpage or application. Users who sympathize or invest in the project will be notified of the progress by email. Users can check detailed progress information in real time via a dedicated dashboard.

[0307] Examples:

[0308] User A inputs and submits her "experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server analyzes the received data using an emotion engine to generate an emotion score. This is then sent to a generative model along with the analyzed emotion data, which is then specifically verbalized as "maternity harassment, being excluded from promotions or work because of pregnancy." The verbalized data and emotion data are saved in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is saved on the server, and progress in solving the problem is regularly updated.

[0309] Example prompt sentence:

[0310] "I feel that I have been harassed at work because I am pregnant. Based on this experience, please appropriately articulate what kind of social issue this is."

[0311] The above is a specific embodiment of the present invention. A system is constructed that recognizes the user's emotions at each processing step and provides appropriate empathy and motivation for investment.

[0312] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0313] Step 1:

[0314] User Input

[0315] Users access the system using a device (smartphone or PC). They enter text about the social issues they face or their personal suffering into an input form on a dedicated webpage or application, and click the submit button. For example, a user might enter "My experience of being harassed at work because of my pregnancy." The input data is sent to the device in text format.

[0316] Input: Text data entered by the user

[0317] Output: Text data is saved to the device.

[0318] Step 2:

[0319] Sending and Receiving Input Data

[0320] The terminal converts the text data entered by the user into JSON format using a JSON encoder running on the terminal, and then sends the converted data to the server using the HTTPS protocol. The server checks the integrity of the received JSON data and prepares it for parsing.

[0321] Input: Text data

[0322] Output: JSON format data

[0323] Specific behavior:

[0324] The device encodes the text data into JSON format.

[0325] The converted JSON data is sent to the server via HTTPS protocol.

[0326] The server verifies the integrity of the data received.

[0327] Step 3:

[0328] Emotional Data Recognition and Analysis

[0329] The server passes the received JSON data to an emotion engine (e.g., IBM Watson or Google Cloud Natural Language API) to analyze the user's emotions. This analysis process extracts emotions (happiness, sadness, anger, etc.) from the text data and generates an emotion score. The server receives the generated emotion score and prepares it for the next step.

[0330] Input: JSON format data

[0331] Output: Sentiment score

[0332] Specific behavior:

[0333] The server passes the JSON data to the emotion engine.

[0334] The emotion engine extracts emotions from the text data and generates an emotion score.

[0335] A server receives the emotion scores from the emotion engine.

[0336] Step 4:

[0337] Data analysis and verbalization

[0338] The server passes the emotion score and analyzed JSON data to a generative AI model (e.g., ChatGPT). The generative AI model then organizes the input issue data into appropriate terms and converts them into specific social issues. For example, "experiences of workplace harassment due to pregnancy" can be verbalized as "maternity harassment, being excluded from promotions or work due to pregnancy."

[0339] Input: sentiment scores, parsed JSON data

[0340] Output: Verbalized text data

[0341] Specific behavior:

[0342] The server sends the sentiment scores and parsed JSON data to the generative AI model.

[0343] The generative AI model organizes the information into appropriate words and verbalizes it as a specific social issue.

[0344] The server receives the verbalized data.

[0345] Step 5:

[0346] Storing and publishing verbalized data

[0347] The server stores the verbalized text data returned by the generative model in a database, converts it into a publicly available format, and displays it on a dedicated web page or application, allowing other users to access and view the information.

[0348] Input: Verbalized text data

[0349] Output: Public data displayed on a dedicated web page or application

[0350] Specific behavior:

[0351] The server stores the verbalized data in a database.

[0352] Convert the stored data into a publishing format (e.g. HTML, JSON).

[0353] The published data will be displayed on special web pages and applications.

[0354] Step 6:

[0355] Seeking sympathy and investment

[0356] Other users can show their support or contribution to the published issue. Users click the "Support" button to send feedback, or click the "Contribute" button to fill out a form and send it to the server from their device. The server processes the received support and contribution data.

[0357] Input: User empathy and investment information

[0358] Output: Sympathy and pledge data stored on the server

[0359] Specific behavior:

[0360] A user views the public data and clicks the sympathy or contribution button.

[0361] Enter your sympathy and investment information and send it from your device to the server.

[0362] The server stores the received data in a database.

[0363] Step 7:

[0364] Management of investment information

[0365] The terminal sends the contribution information entered by the user to the server. The server receives this information and stores it in a database. After confirming that the contribution information has been successfully saved, a thank-you message is sent to the user.

[0366] Input: Investment information

[0367] Output: Contribution information stored in the database, a thank you message

[0368] Specific behavior:

[0369] The terminal transmits the user's contribution information to the server.

[0370] The server stores the investment information in a database.

[0371] Send a thank you message to the user.

[0372] Step 8:

[0373] Progress feedback

[0374] The server periodically updates the progress of the project and displays it on a special webpage and application. Users who sympathize with or invest in the project are notified of the progress by email. Users can also check detailed progress information in real time via a dedicated dashboard.

[0375] Input: Progress information

[0376] Output: Progress information displayed on a dedicated web page or in the application, notification emails sent to users

[0377] Specific behavior:

[0378] The server updates the progress of the issue resolution.

[0379] Display it on a special web page or application.

[0380] Users who have sympathized or invested will be notified of progress via email.

[0381] Users can view progress information on a dedicated dashboard.

[0382] (Application example 2)

[0383] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0384] Previous systems lacked the means to quickly and appropriately verbalize the social challenges and personal suffering they faced and share those experiences with other users. Furthermore, the lack of specific methods for soliciting sympathy and investment, and the lack of clear feedback on progress, weakened users' motivation to solve the problems. Furthermore, the lack of a mechanism for properly recognizing users' emotions made effective analysis difficult.

[0385] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving task data entered by a user, means for transmitting the task data to a generative model and analyzing and verbalizing it, means for saving the verbalized task data in a database, means for generating and publishing the saved task data for display, means for accepting sympathy and contributions for the published task data, means for receiving and saving the sympathy and contribution data, means for generating, publishing, and notifying task-solving progress information, means for receiving task data entered by a user from a smartphone application, and means for generating emotion data by applying the generated data to an emotion analysis engine. This allows the task data entered by a user to be quickly and appropriately verbalized and shared with many users, making it easier to solicit sympathy and contributions and enabling timely feedback on the progress of task solving.

[0386] "User-entered problem data" is text information that describes the social problems and personal difficulties that the user is facing.

[0387] A "generative model" is a model that uses artificial intelligence to analyze input data and appropriately verbalize it in natural language.

[0388] An "emotion analysis engine" is software that analyzes a user's emotions from input text and generates emotional data.

[0389] The "database" is a data storage system for storing and managing verbalized issue data and empathy / investment data.

[0390] "Sympathy and investment" refers to the act of a user emotionally supporting a published issue and providing funds or resources.

[0391] "Progress information" is data that indicates the current status and progress of efforts to solve a problem.

[0392] A "web page" is a page for displaying information that is published on the Internet and can be viewed by users.

[0393] A "dashboard" is an interface that allows users to visually check their progress.

[0394] A "smartphone application" is a software application that runs on a smartphone and is a means by which a user inputs and transmits assignment data.

[0395] The "HTTPS protocol" is an internet protocol for securely transmitting data.

[0396] This invention is a system that allows users to quickly verbalize the social issues and personal suffering they are facing, and solicit sympathy and investment from other users. This system is realized through cooperation between a server, a terminal, and a user.

[0397] 1. User Input

[0398] Users access the system using a smartphone application and input their own problem data, which may include social issues or personal difficulties, such as experiences of harassment at work due to pregnancy. The input data is then sent from the smartphone application to the server.

[0399] 2. Sending and Receiving Data

[0400] The terminal converts the task data entered by the user into JSON format and sends it to the server using the HTTPS protocol. The server prepares the received task data for analysis.

[0401] 3. Emotion analysis and verbalization

[0402] The server runs the received task data through an emotion analysis engine to analyze the user's emotions. For example, emotions such as sadness or anger are extracted from the text and emotion data is generated. The emotion-analyzed data and task data are then sent to a generative AI model, which then translates the data into appropriate language.

[0403] 4. Preservation and publication of verbalized data

[0404] The server stores the verbalized data returned by the generative AI model in a database, which then publishes the data in real time on a special webpage.

[0405] 5. Accepting sympathy and investment

[0406] Other users can express their sympathy for the issue data published on the web page. If they want to donate resources such as time, money, or skills, they can click the contribution button and fill in the appropriate form. This sympathy and contribution data is received by the server and stored in a database.

[0407] 6. Progress Feedback

[0408] The server will periodically update the progress of the project and make it available to users via a special webpage and a dedicated dashboard. Users who have contributed will also be notified of the progress via email.

[0409] Hardware and software used

[0410] Hardware: Smartphone, server (e.g., AWS (registered trademark), GCP)

[0411] Software: Python, Hugging Face Transformers, OpenAI® GPT-3®

[0412] At each step of this system, the user's input data is analyzed and verbalized appropriately through a sentiment analysis engine and a generative AI model, and then published in real time, enabling other users to sympathize with and contribute. As a concrete example, let's use the following prompt sentence.

[0413] Prompt Sentence Examples

[0414] Social Issue: Harassment at Work Because of Pregnancy

[0415] Emotion: [{'label': 'Sad', 'score': 0.95}]

[0416] To put this in words:

[0417] This allows the problem data entered by users to be quickly and appropriately verbalized and shared with many users.The system promotes awareness of problems and functions as a platform for soliciting sympathy and investment to create more effective solutions.

[0418] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0419] Step 1:

[0420] The user starts the smartphone application and inputs their assignment data. For example, the user may enter text about their experience of being harassed at work because of pregnancy. This input data is temporarily saved by the smartphone application.

[0421] input:

[0422] Assignment text (e.g., "I was harassed at work because I was pregnant.")

[0423] output:

[0424] Temporarily saved text data

[0425] Step 2:

[0426] The terminal converts the saved text data into JSON format and sends it to the server using the HTTPS protocol. The converted JSON data contains the text content.

[0427] input:

[0428] Temporarily saved text data

[0429] Data processing:

[0430] Convert text data to JSON format

[0431] output:

[0432] Issue data in JSON format

[0433] Step 3:

[0434] The server receives the assignment data in JSON format sent from the device, and temporarily stores the received data in preparation for analysis.

[0435] input:

[0436] Issue data in JSON format

[0437] output:

[0438] Temporarily saved JSON format issue data

[0439] Step 4:

[0440] The server runs the received task data through a sentiment analysis engine to analyze the user's emotions. The sentiment analysis engine extracts emotions (happiness, sadness, anger, etc.) from the text and generates an emotion score. For example, the emotion "sad" and its score are extracted.

[0441] input:

[0442] Issue data in JSON format

[0443] Data Calculation:

[0444] Sentiment extraction and scoring through text analysis

[0445] output:

[0446] Emotion data (e.g., sad 0.95)

[0447] Step 5:

[0448] The server sends the analyzed emotion data and issue data to the generative AI model, which then verbalizes them appropriately. The generative AI model then organizes the issue data and verbalizes it as a specific social issue. For example, "an experience of being harassed at work because of pregnancy" is verbalized as "an example of maternity harassment is being excluded from promotions or work because of pregnancy."

[0449] input:

[0450] Emotion data and issue data

[0451] Data Calculation:

[0452] Verbalization using generative AI models

[0453] output:

[0454] Verbalized problem data

[0455] Step 6:

[0456] The server stores the verbalized assignment data in a database, after which the assignment data is made public in real time on a special web page.

[0457] input:

[0458] Verbalized problem data

[0459] output:

[0460] Data stored in the database, published assignment data

[0461] Step 7:

[0462] Users can view the issue data published on the webpage and sympathize or contribute. To sympathize, click the "Sympathize" button, and to contribute, click the "Contribute" button and enter the necessary information in the appropriate form. This generates sympathy and contribution data.

[0463] input:

[0464] Published assignment data

[0465] output:

[0466] Empathy or sponsorship data

[0467] Step 8:

[0468] The server receives the empathy and contribution data and stores it in a database. After storing it, the progress of the problem solving is updated and notified to the user.

[0469] input:

[0470] Empathy and investment data

[0471] output:

[0472] Sympathy and investment data stored in database, progress notifications

[0473] Step 9:

[0474] The server will periodically update the progress of the project and make it available to users via a special webpage and a dedicated dashboard. Users who have contributed will also be notified of the progress via email.

[0475] input:

[0476] Progress Information

[0477] output:

[0478] Progress updates, notification emails

[0479] The above are the specific processing steps of the system that realizes the application example.

[0480] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0481] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0482] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0483] [Second embodiment]

[0484] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0485] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0486] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0487] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0488] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0489] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0490] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0491] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0492] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0493] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0494] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0495] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0496] This invention is a system that aims to quickly verbalize the social issues and personal suffering that users are facing, and to widely solicit sympathy and investment. This system is based on cooperation between a server, a terminal, and a user, and is characterized by its ability to appropriately verbalize issues using a generative model.

[0497] System Overview

[0498] 1. User Input

[0499] Users access the system using a device (smartphone or PC). A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. Here, users enter text about the social issues and personal suffering they are facing. Once they have finished entering the text, they press the send button.

[0500] 2. Sending and Receiving Input Data

[0501] The terminal receives the data entered by the user, converts it to JSON format, and then sends the converted data using the HTTPS protocol to the server, which receives the data and prepares it for analysis.

[0502] 3. Data analysis and verbalization

[0503] The server passes the received JSON data to a generative model (such as ChatGPT), which analyzes and verbalizes the data. The generative model then organizes the problem data into appropriate terms and converts it into specific social issues. For example, if the content includes "I am being harassed at work because I am pregnant," this can be verbalized as "An example of maternity harassment is being excluded from promotions or jobs at work because of pregnancy."

[0504] 4. Preservation and publication of verbalized data

[0505] The server stores the verbalized data returned by the generative model in a database, which then converts it into a publicly available format and displays it on a dedicated web page or application, allowing other users to access and view this information.

[0506] 5. Seeking sympathy and investment

[0507] Other users can sympathize with the published challenge. By clicking the "Sympathize" button, users can send their feedback to the system. If users want to contribute their resources (time, money, skills, etc.) to the challenge, they can click the "Contribute" button and fill in the appropriate form.

[0508] 6. Management of investment information

[0509] The terminal sends the user's contribution information to the server. The server receives this information and stores it in a database. Once the contribution information is registered, a thank-you message is sent to the user.

[0510] 7. Progress Feedback

[0511] The server periodically updates the progress of the problem-solving process and displays it on a special webpage and application. Users who have invested or sympathized with the project will be notified of the progress by email. A dedicated dashboard will also be provided, allowing users to check detailed progress information in real time.

[0512] Specific examples

[0513] User A inputs and submits "an experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server then sends the received data to a generative model, which verbalizes it specifically as "maternity harassment, a case where a woman is excluded from promotions or work because of pregnancy." The verbalized data is saved in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is saved on the server, and the progress of problem-solving is regularly updated.

[0514] The above is a specific description of an embodiment of the present invention. This system allows for quick verbalization and recognition of issues, and promotes investment and solutions by communities and individuals.

[0515] The processing flow will be explained below.

[0516] Step 1:

[0517] A user logs in to the system's web page or application using a device (smartphone or PC).

[0518] Step 2:

[0519] Users click the "Post a new social issue" button to access a new entry form, where they can enter the social issues or personal suffering they are facing in the text area.

[0520] Step 3:

[0521] When the user completes the input, they press the "Submit" button, which converts the input data into JSON format data on the device.

[0522] Step 4:

[0523] The device sends this JSON format data to the server using the HTTPS protocol, after which a message indicating successful data transmission is displayed to the user.

[0524] Step 5:

[0525] The server analyzes the received JSON data and extracts necessary fields (user ID, details of the social issue, etc.), and prepares the extracted data for passing to the generative model.

[0526] Step 6:

[0527] The server calls the API of the generative model (such as ChatGPT) and sends the analyzed data. Based on the received data, the generative model verbalizes the social issues in appropriate terms.

[0528] Step 7:

[0529] The generative model returns the verbalized data to the server, for example, "Pregnant employees are harassed at work and excluded from promotions and jobs."

[0530] Step 8:

[0531] The server receives the verbalized data and stores it in the database, logging the success of the save.

[0532] Step 9:

[0533] The server then formats the stored data for public viewing and displays it on a special web page or application, making the information accessible to other users.

[0534] Step 10:

[0535] Users can click the "Sympathize" button for a published issue, or if they want to enter a comment or provide specific support, they can click the "Invest" button and enter the required information.

[0536] Step 11:

[0537] The device converts data related to sympathy and investment into JSON format and sends it back to the server via HTTPS protocol.

[0538] Step 12:

[0539] The server receives the empathy data and the contribution data and stores them in a database. Once the contribution information is saved, a thank you message is sent to the user.

[0540] Step 13:

[0541] The server periodically updates the progress of the problem and displays it on a web page or application, allowing users to check the progress.

[0542] Step 14:

[0543] Users can use a dedicated dashboard to check the progress and new information on the projects they have funded in real time.

[0544] Step 15:

[0545] The server periodically notifies the contributor of the progress by email. This notification is sent automatically according to the timing of updates to the progress status within the system.

[0546] This is the specific processing flow of this system, which enables appropriate verbalization and rapid recognition of social issues, as well as promoting investment and solutions by communities and individuals.

[0547] Example 1

[0548] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0549] In conventional systems, it was difficult for users to quickly and appropriately verbalize the personal or social challenges they faced and to solicit sympathy and investment from other users. In addition, there was a lack of visualization of the progress of the challenges and information provided to investors, making it difficult to provide support for problem-solving efficiently.

[0550] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0551] In this invention, the server includes a means for receiving task data entered by a user, a means for converting the task data into JSON format, and a means for transmitting the converted JSON format data via HTTPS, thereby enabling the task data entered by a user to be quickly and appropriately transmitted to the server for analysis and verbalization.

[0552] "User" refers to an individual or corporation that uses this system to input issue data and sympathize with or invest in the project.

[0553] "Issue data" refers to information entered in text format about social issues or personal problems that users are facing.

[0554] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight text data format that represents data in a structured manner.

[0555] "HTTPS protocol" stands for HyperText Transfer Protocol Secure and refers to an internet protocol for secure communication.

[0556] A "generative AI model" refers to an artificial intelligence model that uses natural language processing to analyze input data and convert it into an appropriate language.

[0557] A "database" refers to a system for organizing and storing information, and for efficiently searching, retrieving, and updating information as needed.

[0558] "Publication format" refers to a format in which data has been converted into a form that can be viewed by other users, such as HTML or JSON.

[0559] "Empathy" refers to the act of users expressing emotional reactions to published assignment data and sending feedback.

[0560] "Investment" refers to the act of a user providing their own resources (time, money, skills, etc.) to solve a problem.

[0561] A "staging area" refers to an area where received data is temporarily stored and its format and content are validated.

[0562] "Validation" refers to the process of checking whether the content of data is accurate and valid.

[0563] "Dedicated form" refers to a special input screen provided within the system for users to input assignment data.

[0564] The "thank you message" refers to a message sent from the server to the user who made the investment, expressing gratitude.

[0565] A "dashboard" refers to a visual interface that allows users to check the progress of problem-solving in real time.

[0566] A "scheduler" refers to a program that executes a specific process at a fixed time.

[0567] This invention is a system that operates in cooperation with the user, the terminal, and the server. Specifically, it quickly analyzes the problem data entered by the user, properly verbalizes it, and then publishes it, thereby streamlining the process of soliciting sympathy and investment.

[0568] System Configuration

[0569] User Input

[0570] Users access the system using a device (smartphone or PC). They can enter the social issues and personal suffering they are facing in text format through a dedicated web page or application. This input is saved at regular intervals using an auto-save function. After completing the input, the user clicks the send button, and the data is converted into JSON format and sent to the server using the HTTPS protocol.

[0571] Sending and Receiving Data

[0572] The terminal converts the data entered by the user into JSON format and sends it to the server via the HTTPS protocol. The server temporarily stores the received data in a staging area and validates the data to ensure that its format and content are appropriate.

[0573] Data analysis and verbalization

[0574] The server formats the JSON data stored in the staging area so that it can be used by a generative AI model (e.g., ChatGPT). This formatted data is passed to the generative model, which analyzes the data and verbalizes the problem. For example, if an input is "I am being harassed at work because I am pregnant," the generative model verbalizes this as "An example of maternity harassment is being excluded from promotions or work because of pregnancy."

[0575] Storing and publishing verbalized data

[0576] The server stores the verbalized data returned by the generative model in a database. This stored data can then be converted into a publicly available format (e.g., HTML or JSON) and displayed on a dedicated web page or application. This process allows other users to access and view this information.

[0577] Seeking sympathy and investment

[0578] Other users can express their "sympathy" for the published challenge. Users who want to express their sympathy click the "Sympathy" button, and their feedback is sent from their device to the server. Users can also click the "Invest" button and enter details of their resources, such as time, money, or skills, into a dedicated form. This information is also sent from their device to the server.

[0579] Management of investment information

[0580] The terminal converts the user's contribution information into JSON format and sends it to the server via HTTPS. After receiving the contribution information, the server validates it and stores it in the database. After the contribution is completed, a thank-you message is sent to the user.

[0581] Progress feedback

[0582] The server periodically updates the progress of the problem-solving process. This progress information is retrieved from the database and displayed on a dedicated web page or application. Users who have contributed or sympathized with the project are also notified of the progress via email. A system is also provided that allows users to check progress information in real time via a dedicated dashboard.

[0583] Prompt Sentence Examples

[0584] Please explain in detail the harassment you have experienced in the workplace.

[0585] The above is a specific embodiment of the present invention, which enables a user to quickly and appropriately verbalize the issues they face and solicit sympathy and investment from other users.

[0586] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0587] Step 1:

[0588] Users log in to the system using their own device (smartphone or PC). They enter the social issues and personal suffering they are facing in text format into a dedicated form. The input information is automatically saved at regular intervals. Once the input is complete, the user clicks the send button.

[0589] Input: User-entered assignment data (text format)

[0590] Output: Send instructions are generated on the user's terminal

[0591] Step 2:

[0592] The terminal receives the task data entered by the user, converts it into JSON format, and sends the converted data to the server using the HTTPS protocol.

[0593] Input: User-entered assignment data (text format)

[0594] Data processing: Converting issue data into JSON format

[0595] Output: JSON format data is sent to the server

[0596] Step 3:

[0597] The server temporarily stores the JSON data received via HTTPS in a staging area, where the format and content of the data are validated.

[0598] Input: Issue data in JSON format

[0599] Data processing: Validating the format and content of JSON data

[0600] Output: Pass validated JSON data to the generated AI model

[0601] Step 4:

[0602] The server passes the validated JSON data to a generative AI model (e.g., ChatGPT), which analyzes and verbalizes the data. The generative model then organizes the input data into appropriate terms and converts them into specific social issues. For example, if an input states, "I am being harassed at work because I am pregnant," the generative model verbalizes this as, "An example of maternity harassment is being excluded from promotions or jobs at work because of pregnancy."

[0603] Input: Validated JSON data

[0604] Data Computation: Data Analysis and Verbalization with Generative AI Models

[0605] Output: Verbalized task data

[0606] Step 5:

[0607] The server stores the verbalized data returned by the generative AI model in a database, converts the stored data into a publicly available format (e.g., HTML, JSON), and displays it on a dedicated webpage or application.

[0608] Input: Verbalized task data

[0609] Data processing: converting data into a format for publication

[0610] Output: Data displayed on a dedicated web page or application

[0611] Step 6:

[0612] Other users can express their sympathy for the published problem data. By clicking the "Sympathize" button, feedback is sent from the device to the server. Users can also click the "Invest" button and enter details of their resources, such as time, money, or skills, into a dedicated form. This information is also sent from the device to the server.

[0613] Input: The like or pledge button the user clicked

[0614] Data processing: Sending feedback or contribution information

[0615] Output: Empathy or pledge data sent to the server

[0616] Step 7:

[0617] The server receives the sympathy and contribution data, validates the contents, and stores them in the database. After the contribution is completed, a thank you message is sent to the user.

[0618] Input: Empathy data, investment data

[0619] Data processing: validation and saving to database

[0620] Output: Validated empathy data, pledge data, and a thank you message

[0621] Step 8:

[0622] The server periodically updates the progress of the project. This progress information is retrieved from the database and displayed on a dedicated web page or application. Users who have contributed or sympathized are notified of the progress by email, and can check the progress information in real time through a dedicated dashboard.

[0623] Input: Progress information in the database

[0624] Data processing: Updating and obtaining progress information

[0625] Output: Publishing and notifying progress updates

[0626] (Application example 1)

[0627] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0628] Conventional problem-solving systems lacked sufficient means for users to quickly verbalize the social issues and personal suffering they faced and then share that information widely. Furthermore, they lacked a means to create advertisements based on verbalized problem data and efficiently solicit sympathy and investment, making it difficult to effectively gather support for problem-solving. For this reason, a new system was needed to quickly and effectively solve users' problems across society.

[0629] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0630] In this invention, the server includes means for transmitting problem data entered by the user to a generative model for analysis and verbalization, means for embedding the generated verbalized data in an advertising template to generate an advertisement, and means for distributing the generated advertisement to social media and websites. This makes it possible to quickly share users' problems and generate advertisements based on them to effectively attract sympathy and investment.

[0631] A "user" is an individual or organization that inputs assignment data and shares that assignment through the system.

[0632] "Issue data" is text data that expresses the social issues and personal suffering that users are facing.

[0633] A "generative model" is an artificial intelligence model that analyzes input task data and converts it into appropriate words.

[0634] "Verbalized data" is task data that has been analyzed by a generative model and converted into an appropriate format.

[0635] An "advertising template" is a model of an advertisement prepared for embedding generated verbalized data.

[0636] "Advertising" refers to content generated based on verbalized data and distributed on social media and websites.

[0637] "Social media" is a general term for online platforms through which users receive advertising.

[0638] A "Website" is an online page for displaying advertisements on the Internet.

[0639] "Empathy" is an act in which other users show emotional understanding and support for a published issue.

[0640] "Contribution" is the act of a user providing resources such as time, money, or skills to a published challenge.

[0641] "Progress information" is data that indicates the progress of problem solving and the current situation.

[0642] "Advertising status management" is the process of monitoring and controlling the status of advertising on social media and websites.

[0643] This invention is a system that allows users to quickly verbalize social issues and personal suffering they are facing and share that information widely. This system aims to effectively attract sympathy and investment by creating advertisements based on the generated verbalization data through collaboration between users, devices, generative models, and servers.

[0644] System Overview

[0645] 1. User input:

[0646] Users access the system using devices such as smartphones or PCs. A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. The text entered in this form is treated as assignment data.

[0647] 2. Receiving and sending assignment data:

[0648] The terminal receives the assignment data entered by the user, converts it into JSON format, and then sends the converted data to the server using the HTTPS protocol.

[0649] 3. Data analysis and verbalization:

[0650] The server passes the received JSON data to a generative model (such as ChatGPT) to analyze and verbalize the data. The generative model then organizes and converts the problem data into appropriate language, converting it into specific social issues.

[0651] 4. Ad generation and delivery:

[0652] The server embeds the generated verbalized data into an advertising template, which generates an advertisement designed to resonate with users. The generated advertisement is then distributed to social media and websites. The server also collects and analyzes user feedback on the advertisement to evaluate its effectiveness.

[0653] 5. Empathy and stake management:

[0654] Other users can express their sympathy for the published issues. Data on sympathy and contributions is also sent to the server and stored in a database. The server periodically updates the progress of the issue and notifies the contributors and other stakeholders by email.

[0655] Specific examples

[0656] For example, User A inputs her experience of "being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server then sends this data to a generative model, which verbalizes it specifically as "problems related to maternity harassment in the workplace." The verbalized data is embedded in an ad template, and an ad is automatically generated that reads, "(Relatable ad) Problem: Maternity harassment is occurring in the workplace. We need your support. Learn more: www.example.com / donate." This ad is then distributed on social media and websites, and feedback is collected.

[0657] Prompt Sentence Examples

[0658] An example of an input prompt for a generative AI model is as follows:

[0659] "Verbalize the following user input for advertising: I am being harassed at work because I am pregnant"

[0660] The above description provides a detailed explanation of how the present invention can be implemented, allowing users to quickly articulate the challenges they face and gain widespread sympathy and investment.

[0661] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0662] Step 1:

[0663] Users access a dedicated web page or application using a device such as a smartphone or PC and input their experiences and thoughts. The input data is treated as assignment data. In this case, the text data entered by the user becomes input data to be passed on to the next processing step.

[0664] Step 2:

[0665] The terminal receives the assignment data entered by the user and converts it into JSON format. The converted data is sent to the server using the HTTPS protocol. Here, the input is the assignment data and the output is JSON format data.

[0666] Step 3:

[0667] The server passes the received JSON data to a generative model, which analyzes and verbalizes the data. The generative model (such as ChatGPT) organizes and converts the task data into appropriate language. The input for this process is JSON data, and the output is verbalized data. Specific data processing involves analyzing the task data and converting it into appropriate language expressions.

[0668] Step 4:

[0669] The server embeds the generated verbalized data into an advertising template. The advertising template is a pre-prepared format, and specific advertising content is generated by embedding the verbalized data. The inputs to this process are the verbalized data and the advertising template, and the output is the generated advertisement. Specifically, the verbalized data is inserted into a placeholder in the template.

[0670] Step 5:

[0671] The server distributes the generated advertisements to social media platforms and websites. After the advertisements are distributed, users can provide feedback on the advertisements. The input of this process is the generated advertisement, and the output is the distributed advertisement and user feedback. Specifically, the advertisements are sent to social media APIs and the website's advertisement management system.

[0672] Step 6:

[0673] The server collects and analyzes user responses to advertisements from social media and websites. The effectiveness of the advertisements is evaluated based on the collected feedback data. The input to this process is the feedback data, and the output is the analysis results. Specifically, the feedback data is stored in a database and statistical analysis and text mining are performed.

[0674] Step 7:

[0675] Other users can express their support or investment in the published issues. The server also receives this data and stores it in a database. Based on the support and investment data, progress information on the issue resolution is generated, updated periodically, and notified to investors and related parties via email. The input to this process is support and investment data, and the output is progress information and notification emails. Specifically, the support and investment data is analyzed, progress information is generated, and notifications are sent using the email system.

[0676] The above are the specific processing steps of the program for the system that realizes the application example.

[0677] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0678] This invention is a system that aims to quickly verbalize the social issues and personal suffering faced by users, and to widely solicit sympathy and investment. This system is based on collaboration between a server, a device, and a user, and is characterized by its ability to appropriately verbalize issues using a generative model. In addition, by combining it with an emotion engine that recognizes the user's emotions, it enables more accurate analysis and more effective motivation for sympathy and investment.

[0679] System Overview

[0680] 1. User Input

[0681] Users access the system using a device (smartphone or PC). A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. Here, users enter text about the social issues and personal suffering they are facing. Once they have finished entering the text, they press the send button.

[0682] 2. Sending and Receiving Input Data

[0683] The terminal receives the data entered by the user, converts it to JSON format, and then sends the converted data using the HTTPS protocol to the server, which receives the data and prepares it for analysis.

[0684] 3. Emotion Data Recognition and Analysis

[0685] The server applies an emotion engine to the received JSON data to analyze the user's emotions. For example, it extracts emotions (happiness, sadness, anger, etc.) from the text data and generates an emotion score.

[0686] 4. Data analysis and verbalization

[0687] Taking the analyzed emotion data into consideration, the server passes the received JSON data to a generative model (such as ChatGPT) for data analysis and verbalization. The generative model then organizes the problem data into appropriate terms and converts it into a specific social issue. For example, a statement such as "A pregnant employee was harassed at work and excluded from promotions and work" can be verbalized as "An example of maternity harassment is being excluded from promotions and work due to pregnancy."

[0688] 5. Preservation and publication of verbalized data

[0689] The server stores the verbalized and emotional data returned by the generative model in a database, which then converts the data into a publicly available format and displays it on a dedicated web page or application, allowing other users to access and view the information.

[0690] 6. Seeking sympathy and investment

[0691] Other users can sympathize with the published challenge. By clicking the "Sympathize" button, users can send their feedback to the system. If users want to contribute their resources (time, money, skills, etc.) to the challenge, they can click the "Contribute" button and fill in the appropriate form.

[0692] 7. Management of investment information

[0693] The terminal sends the user's contribution information to the server. The server receives this information and stores it in a database. Once the contribution information is registered, a thank-you message is sent to the user.

[0694] 8. Progress Feedback

[0695] The server periodically updates the progress of the problem-solving process and displays it on a special webpage and application. Users who have invested or sympathized with the project will be notified of the progress by email. A dedicated dashboard will also be provided, allowing users to check detailed progress information in real time.

[0696] Specific examples

[0697] User A inputs and submits her "experience of workplace harassment due to pregnancy." This data is converted to JSON format and sent to the server via HTTPS protocol. The server analyzes the received data through an emotion engine and generates an emotion score. This is then sent to the generative model along with the analyzed emotion data, which is then specifically verbalized as "maternity harassment, a case where a woman is excluded from promotions or work due to pregnancy." The verbalized data and emotion data are stored in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is stored on the server, and the progress of problem-solving is regularly updated.

[0698] The above is a specific description of an embodiment of the present invention. This system enables quick verbalization and recognition of issues, and promotes investment and solutions by communities and individuals. Furthermore, by recognizing the user's emotions, it is possible to empathize more effectively and motivate investment.

[0699] The processing flow will be explained below.

[0700] Step 1:

[0701] A user logs in to the system's web page or application using a device (smartphone or PC).

[0702] Step 2:

[0703] The user clicks the "Post a new social issue" button to access a new entry form. Here, the user enters the social issue or personal suffering they are facing into the text area. For example, the user could provide details such as "I was harassed at work because I am pregnant."

[0704] Step 3:

[0705] When the user completes the input, they press the "Submit" button, which converts the input data into JSON format data on the device.

[0706] Step 4:

[0707] The device sends this JSON format data to the server using the HTTPS protocol, after which a message indicating successful data transmission is displayed to the user.

[0708] Step 5:

[0709] The server analyzes the received JSON data and extracts necessary fields (user ID, details of the social issue, etc.), and prepares the extracted data for passing to the generative model.

[0710] Step 6:

[0711] The server sends the task data to the emotion engine, which extracts emotions from the text data and generates an emotion score (e.g., ranging from 0 to 1 representing joy, sadness, anger, etc.).

[0712] Step 7:

[0713] The analyzed data, along with the emotion score generated by the server, is sent to a generative model (e.g., ChatGPT) for analysis and verbalization. The generative model then organizes the issue data into concrete terms and converts it into a social issue. For example, "I was harassed at work because I was pregnant" is verbalized as "An example of maternity harassment is when a woman is excluded from promotions or jobs at work because she is pregnant."

[0714] Step 8:

[0715] The server saves the verbalized data and sentiment scores returned by the generative model to a database, and logs the success of the save.

[0716] Step 9:

[0717] The server then formats the stored data for public viewing and displays it on a special web page or application, making the information accessible to other users.

[0718] Step 10:

[0719] Users can click the "Sympathize" button for a published issue, or if they want to enter a comment or provide specific support, they can click the "Invest" button and enter the required information.

[0720] Step 11:

[0721] The device converts data related to sympathy and investment into JSON format and sends it back to the server via HTTPS protocol.

[0722] Step 12:

[0723] The server receives the empathy data and the contribution data and stores them in a database. Once the contribution information is saved, a thank you message is sent to the user.

[0724] Step 13:

[0725] The server periodically updates the progress of the problem and displays it on a web page or application, allowing users to check the progress.

[0726] Step 14:

[0727] Users can use a dedicated dashboard to check the progress and new information on the projects they have funded in real time.

[0728] Step 15:

[0729] The server periodically notifies the contributor of the progress by email. This notification is sent automatically according to the timing of updates to the progress status within the system.

[0730] As a concrete example, User A inputs and submits "an experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server analyzes the received data using an emotion engine to generate an emotion score. This is then sent to the generative model along with the analyzed emotion data, which is specifically verbalized as "maternity harassment, a case where a woman is excluded from promotions or work because of pregnancy." The verbalized data and emotion data are stored in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and makes an additional investment of 1,000 yen. This information is stored on the server, and the progress of problem-solving is regularly updated.

[0731] The above is the specific processing flow of this system. This enables appropriate verbalization and rapid recognition of social issues, as well as promoting investment and solutions by communities and individuals. Furthermore, the introduction of an emotion engine enables analysis that takes into account the user's emotions and expands empathy.

[0732] Example 2

[0733] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0734] In modern society, there is a lack of ways for individuals to quickly verbalize the social issues and personal suffering they face and to solicit widespread sympathy and investment. As a result, individual problems are not easily recognized by society, and it takes a long time to receive effective support. Furthermore, the lack of a system that can appropriately handle users' emotions means that there is insufficient motivation for empathy and investment.

[0735] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0736] In this invention, the server includes means for receiving task data entered by a user, means for converting the received task data into JSON format, means for transmitting the converted data via HTTPS protocol, means for analyzing the task data and generating an emotional score, means for transmitting the analyzed emotional score and task data to a generative AI model for analysis and verbalization, means for saving the verbalized task data in a database, means for generating and publishing the saved task data for display, means for accepting sympathy and contributions for the published task data, means for receiving and saving the sympathy and contribution data, and means for generating, publishing, and notifying progress information on problem solving. This enables the task data to be quickly verbalized and widely shared, and motivates sympathy and contributions.

[0737] "User" refers to any individual or entity that uses the System.

[0738] "Issue data" refers to text data entered by users about social issues or personal suffering.

[0739] "JSON format" refers to a JavaScript Object Notation data structure, a text format used for exchanging and storing data.

[0740] The "HTTPS protocol" is a communication protocol for securely transferring data over the Internet.

[0741] "Emotion score" refers to a numerical representation of the type and intensity of emotions extracted from text data.

[0742] A "generative AI model" refers to an artificial intelligence algorithm that uses a large-scale language model to parse and verbalize data.

[0743] A "database" refers to a system for efficiently storing, managing, and searching large amounts of data.

[0744] "Publication" refers to making the stored data publicly available for viewing via the Internet.

[0745] "Empathy" refers to the act of other users showing sympathy or understanding for a published issue.

[0746] "Contribution" refers to the act of other users providing resources (funds, time, skills, etc.) to a published challenge.

[0747] "Thank you message" refers to a message of gratitude sent from the server when a user makes a contribution.

[0748] "Progress information" refers to data regarding the progress of activities toward resolving a problem.

[0749] A "dashboard" refers to an interface designed to allow users to see the status and progress of a system at a glance.

[0750] This invention is a system that aims to quickly verbalize the social issues and personal suffering faced by users, and to widely solicit sympathy and investment. The system is based on three-way collaboration between a server, a terminal, and a user. This enables the appropriate verbalization of issues using a generative AI model, combined with an emotion engine that recognizes the user's emotions, enabling more accurate analysis and effective motivation for sympathy and investment. The specific hardware and software used will be explained in turn.

[0751] First, the user accesses the system using a terminal. The terminal can be a smartphone or personal computer, and a form is provided for the user to enter their experiences and thoughts. The user enters the assignment data through a dedicated web page or application and presses the submit button.

[0752] The device receives the text data entered by the user and converts it into JSON format. It then sends it to the server using the HTTPS protocol. The server prepares the received JSON data for analysis. Specifically, the server uses an emotion engine (e.g., IBM Watson or Google Cloud Natural Language API) to analyze the user's emotions. This process extracts emotions such as joy, sadness, and anger from the entered text data and generates an emotion score.

[0753] The server then passes the analyzed emotion data and issue data to a generative AI model (such as ChatGPT). The generative AI model then organizes the given issue data into appropriate language and converts it into a specific social issue. For example, a statement such as "A pregnant employee was harassed at work and excluded from promotions and work" can be verbalized as "Maternity harassment involves being excluded from promotions and work due to pregnancy."

[0754] The server stores the verbalized data in a database, converts the data into a public format, and instantly publishes it on a special web page or application, allowing other users to view the information.

[0755] Other users can show their support or investment in the published challenge. By clicking the "Support" button, users can send feedback to the system. Also, by clicking the "Invest" button, users who want to donate their resources (time, money, skills, etc.) can fill out the appropriate form and send it from their device to the server. The server stores the received investment information in a database and manages it.

[0756] Furthermore, the server periodically updates the progress of the project and displays it on a special webpage or application. Users who sympathize or invest in the project will be notified of the progress by email. Users can check detailed progress information in real time via a dedicated dashboard.

[0757] Examples:

[0758] User A inputs and submits her "experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server analyzes the received data using an emotion engine to generate an emotion score. This is then sent to a generative model along with the analyzed emotion data, which is then specifically verbalized as "maternity harassment, being excluded from promotions or work because of pregnancy." The verbalized data and emotion data are saved in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is saved on the server, and progress in solving the problem is regularly updated.

[0759] Example prompt sentence:

[0760] "I feel that I have been harassed at work because I am pregnant. Based on this experience, please appropriately articulate what kind of social issue this is."

[0761] The above is a specific embodiment of the present invention. A system is constructed that recognizes the user's emotions at each processing step and provides appropriate empathy and motivation for investment.

[0762] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0763] Step 1:

[0764] User Input

[0765] Users access the system using a device (smartphone or PC). They enter text about the social issues they face or their personal suffering into an input form on a dedicated webpage or application, and click the submit button. For example, a user might enter "My experience of being harassed at work because of my pregnancy." The input data is sent to the device in text format.

[0766] Input: Text data entered by the user

[0767] Output: Text data is saved to the device.

[0768] Step 2:

[0769] Sending and Receiving Input Data

[0770] The terminal converts the text data entered by the user into JSON format using a JSON encoder running on the terminal, and then sends the converted data to the server using the HTTPS protocol. The server checks the integrity of the received JSON data and prepares it for parsing.

[0771] Input: Text data

[0772] Output: JSON format data

[0773] Specific behavior:

[0774] The device encodes the text data into JSON format.

[0775] The converted JSON data is sent to the server via HTTPS protocol.

[0776] The server verifies the integrity of the data received.

[0777] Step 3:

[0778] Emotional Data Recognition and Analysis

[0779] The server passes the received JSON data to an emotion engine (e.g., IBM Watson or Google Cloud Natural Language API) to analyze the user's emotions. This analysis process extracts emotions (happiness, sadness, anger, etc.) from the text data and generates an emotion score. The server receives the generated emotion score and prepares it for the next step.

[0780] Input: JSON format data

[0781] Output: Sentiment score

[0782] Specific behavior:

[0783] The server passes the JSON data to the emotion engine.

[0784] The emotion engine extracts emotions from the text data and generates an emotion score.

[0785] A server receives the emotion scores from the emotion engine.

[0786] Step 4:

[0787] Data analysis and verbalization

[0788] The server passes the emotion score and analyzed JSON data to a generative AI model (e.g., ChatGPT). The generative AI model then organizes the input issue data into appropriate terms and converts them into specific social issues. For example, "experiences of workplace harassment due to pregnancy" can be verbalized as "maternity harassment, being excluded from promotions or work due to pregnancy."

[0789] Input: sentiment scores, parsed JSON data

[0790] Output: Verbalized text data

[0791] Specific behavior:

[0792] The server sends the sentiment scores and parsed JSON data to the generative AI model.

[0793] The generative AI model organizes the information into appropriate words and verbalizes it as a specific social issue.

[0794] The server receives the verbalized data.

[0795] Step 5:

[0796] Storing and publishing verbalized data

[0797] The server stores the verbalized text data returned by the generative model in a database, converts it into a publicly available format, and displays it on a dedicated web page or application, allowing other users to access and view the information.

[0798] Input: Verbalized text data

[0799] Output: Public data displayed on a dedicated web page or application

[0800] Specific behavior:

[0801] The server stores the verbalized data in a database.

[0802] Convert the stored data into a publishing format (e.g. HTML, JSON).

[0803] The published data will be displayed on special web pages and applications.

[0804] Step 6:

[0805] Seeking sympathy and investment

[0806] Other users can show their support or contribution to the published issue. Users click the "Support" button to send feedback, or click the "Contribute" button to fill out a form and send it to the server from their device. The server processes the received support and contribution data.

[0807] Input: User empathy and investment information

[0808] Output: Sympathy and pledge data stored on the server

[0809] Specific behavior:

[0810] A user views the public data and clicks the sympathy or contribution button.

[0811] Enter your sympathy and investment information and send it from your device to the server.

[0812] The server stores the received data in a database.

[0813] Step 7:

[0814] Management of investment information

[0815] The terminal sends the contribution information entered by the user to the server. The server receives this information and stores it in a database. After confirming that the contribution information has been successfully saved, a thank-you message is sent to the user.

[0816] Input: Investment information

[0817] Output: Contribution information stored in the database, a thank you message

[0818] Specific behavior:

[0819] The terminal transmits the user's contribution information to the server.

[0820] The server stores the investment information in a database.

[0821] Send a thank you message to the user.

[0822] Step 8:

[0823] Progress feedback

[0824] The server periodically updates the progress of the project and displays it on a special webpage and application. Users who sympathize with or invest in the project are notified of the progress by email. Users can also check detailed progress information in real time via a dedicated dashboard.

[0825] Input: Progress information

[0826] Output: Progress information displayed on a dedicated web page or in the application, notification emails sent to users

[0827] Specific behavior:

[0828] The server updates the progress of the issue resolution.

[0829] Display it on a special web page or application.

[0830] Users who have sympathized or invested will be notified of progress via email.

[0831] Users can view progress information on a dedicated dashboard.

[0832] (Application example 2)

[0833] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0834] Previous systems lacked the means to quickly and appropriately verbalize the social challenges and personal suffering they faced and share those experiences with other users. Furthermore, the lack of specific methods for soliciting sympathy and investment, and the lack of clear feedback on progress, weakened users' motivation to solve the problems. Furthermore, the lack of a mechanism for properly recognizing users' emotions made effective analysis difficult.

[0835] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving task data entered by a user, means for transmitting the task data to a generative model and analyzing and verbalizing it, means for saving the verbalized task data in a database, means for generating and publishing the saved task data for display, means for accepting sympathy and contributions for the published task data, means for receiving and saving the sympathy and contribution data, means for generating, publishing, and notifying task-solving progress information, means for receiving task data entered by a user from a smartphone application, and means for generating emotion data by applying the generated data to an emotion analysis engine. This allows the task data entered by a user to be quickly and appropriately verbalized and shared with many users, making it easier to solicit sympathy and contributions and enabling timely feedback on the progress of task solving.

[0836] "User-entered problem data" is text information that describes the social problems and personal difficulties that the user is facing.

[0837] A "generative model" is a model that uses artificial intelligence to analyze input data and appropriately verbalize it in natural language.

[0838] An "emotion analysis engine" is software that analyzes a user's emotions from input text and generates emotional data.

[0839] The "database" is a data storage system for storing and managing verbalized issue data and empathy / investment data.

[0840] "Sympathy and investment" refers to the act of a user emotionally supporting a published issue and providing funds or resources.

[0841] "Progress information" is data that indicates the current status and progress of efforts to solve a problem.

[0842] A "web page" is a page for displaying information that is published on the Internet and can be viewed by users.

[0843] A "dashboard" is an interface that allows users to visually check their progress.

[0844] A "smartphone application" is a software application that runs on a smartphone and is a means by which a user inputs and transmits assignment data.

[0845] The "HTTPS protocol" is an internet protocol for securely transmitting data.

[0846] This invention is a system that allows users to quickly verbalize the social issues and personal suffering they are facing, and solicit sympathy and investment from other users. This system is realized through cooperation between a server, a terminal, and a user.

[0847] 1. User Input

[0848] Users access the system using a smartphone application and input their own problem data, which may include social issues or personal difficulties, such as experiences of harassment at work due to pregnancy. The input data is then sent from the smartphone application to the server.

[0849] 2. Sending and Receiving Data

[0850] The terminal converts the task data entered by the user into JSON format and sends it to the server using the HTTPS protocol. The server prepares the received task data for analysis.

[0851] 3. Emotion analysis and verbalization

[0852] The server runs the received task data through an emotion analysis engine to analyze the user's emotions. For example, emotions such as sadness or anger are extracted from the text and emotion data is generated. The emotion-analyzed data and task data are then sent to a generative AI model, which then translates the data into appropriate language.

[0853] 4. Preservation and publication of verbalized data

[0854] The server stores the verbalized data returned by the generative AI model in a database, which then publishes the data in real time on a special webpage.

[0855] 5. Accepting sympathy and investment

[0856] Other users can express their sympathy for the issue data published on the web page. If they want to donate resources such as time, money, or skills, they can click the contribution button and fill in the appropriate form. This sympathy and contribution data is received by the server and stored in a database.

[0857] 6. Progress Feedback

[0858] The server will periodically update the progress of the project and make it available to users via a special webpage and a dedicated dashboard. Users who have contributed will also be notified of the progress via email.

[0859] Hardware and software used

[0860] Hardware: Smartphone, Server (e.g. AWS, GCP)

[0861] Software: Python, Hugging Face Transformers, OpenAI GPT-3

[0862] At each step of this system, the user's input data is analyzed and verbalized appropriately through a sentiment analysis engine and a generative AI model, and then published in real time, enabling other users to sympathize with and contribute. As a concrete example, let's use the following prompt sentence.

[0863] Prompt Sentence Examples

[0864] Social Issue: Harassment at Work Because of Pregnancy

[0865] Emotion: [{'label': 'Sad', 'score': 0.95}]

[0866] To put this in words:

[0867] This allows the problem data entered by users to be quickly and appropriately verbalized and shared with many users.The system promotes awareness of problems and functions as a platform for soliciting sympathy and investment to create more effective solutions.

[0868] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0869] Step 1:

[0870] The user starts the smartphone application and inputs their assignment data. For example, the user may enter text about their experience of being harassed at work because of pregnancy. This input data is temporarily saved by the smartphone application.

[0871] input:

[0872] Assignment text (e.g., "I was harassed at work because I was pregnant.")

[0873] output:

[0874] Temporarily saved text data

[0875] Step 2:

[0876] The terminal converts the saved text data into JSON format and sends it to the server using the HTTPS protocol. The converted JSON data contains the text content.

[0877] input:

[0878] Temporarily saved text data

[0879] Data processing:

[0880] Convert text data to JSON format

[0881] output:

[0882] Issue data in JSON format

[0883] Step 3:

[0884] The server receives the assignment data in JSON format sent from the device, and temporarily stores the received data in preparation for analysis.

[0885] input:

[0886] Issue data in JSON format

[0887] output:

[0888] Temporarily saved JSON format issue data

[0889] Step 4:

[0890] The server runs the received task data through a sentiment analysis engine to analyze the user's emotions. The sentiment analysis engine extracts emotions (happiness, sadness, anger, etc.) from the text and generates an emotion score. For example, the emotion "sad" and its score are extracted.

[0891] input:

[0892] Issue data in JSON format

[0893] Data Calculation:

[0894] Sentiment extraction and scoring through text analysis

[0895] output:

[0896] Emotion data (e.g., sad 0.95)

[0897] Step 5:

[0898] The server sends the analyzed emotion data and issue data to the generative AI model, which then verbalizes them appropriately. The generative AI model then organizes the issue data and verbalizes it as a specific social issue. For example, "an experience of being harassed at work because of pregnancy" is verbalized as "an example of maternity harassment is being excluded from promotions or work because of pregnancy."

[0899] input:

[0900] Emotion data and issue data

[0901] Data Calculation:

[0902] Verbalization using generative AI models

[0903] output:

[0904] Verbalized problem data

[0905] Step 6:

[0906] The server stores the verbalized assignment data in a database, after which the assignment data is made public in real time on a special web page.

[0907] input:

[0908] Verbalized problem data

[0909] output:

[0910] Data stored in the database, published assignment data

[0911] Step 7:

[0912] Users can view the issue data published on the webpage and sympathize or contribute. To sympathize, click the "Sympathize" button, and to contribute, click the "Contribute" button and enter the necessary information in the appropriate form. This generates sympathy and contribution data.

[0913] input:

[0914] Published assignment data

[0915] output:

[0916] Empathy or sponsorship data

[0917] Step 8:

[0918] The server receives the empathy and contribution data and stores it in a database. After storing it, the progress of the problem solving is updated and notified to the user.

[0919] input:

[0920] Empathy and investment data

[0921] output:

[0922] Sympathy and investment data stored in database, progress notifications

[0923] Step 9:

[0924] The server will periodically update the progress of the project and make it available to users via a special webpage and a dedicated dashboard. Users who have contributed will also be notified of the progress via email.

[0925] input:

[0926] Progress Information

[0927] output:

[0928] Progress updates, notification emails

[0929] The above are the specific processing steps of the system that realizes the application example.

[0930] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0931] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0932] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0933] [Third embodiment]

[0934] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0935] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0936] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0937] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0938] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0939] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0940] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0941] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0942] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0943] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0944] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0945] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0946] This invention is a system that aims to quickly verbalize the social issues and personal suffering that users are facing, and to widely solicit sympathy and investment. This system is based on cooperation between a server, a terminal, and a user, and is characterized by its ability to appropriately verbalize issues using a generative model.

[0947] System Overview

[0948] 1. User Input

[0949] Users access the system using a device (smartphone or PC). A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. Here, users enter text about the social issues and personal suffering they are facing. Once they have finished entering the text, they press the send button.

[0950] 2. Sending and Receiving Input Data

[0951] The terminal receives the data entered by the user, converts it to JSON format, and then sends the converted data using the HTTPS protocol to the server, which receives the data and prepares it for analysis.

[0952] 3. Data analysis and verbalization

[0953] The server passes the received JSON data to a generative model (such as ChatGPT), which analyzes and verbalizes the data. The generative model then organizes the problem data into appropriate terms and converts it into specific social issues. For example, if the content includes "I am being harassed at work because I am pregnant," this can be verbalized as "An example of maternity harassment is being excluded from promotions or jobs at work because of pregnancy."

[0954] 4. Preservation and publication of verbalized data

[0955] The server stores the verbalized data returned by the generative model in a database, which then converts it into a publicly available format and displays it on a dedicated web page or application, allowing other users to access and view this information.

[0956] 5. Seeking sympathy and investment

[0957] Other users can sympathize with the published challenge. By clicking the "Sympathize" button, users can send their feedback to the system. If users want to contribute their resources (time, money, skills, etc.) to the challenge, they can click the "Contribute" button and fill in the appropriate form.

[0958] 6. Management of investment information

[0959] The terminal sends the user's contribution information to the server. The server receives this information and stores it in a database. Once the contribution information is registered, a thank-you message is sent to the user.

[0960] 7. Progress Feedback

[0961] The server periodically updates the progress of the problem-solving process and displays it on a special webpage and application. Users who have invested or sympathized with the project will be notified of the progress by email. A dedicated dashboard will also be provided, allowing users to check detailed progress information in real time.

[0962] Specific examples

[0963] User A inputs and submits "an experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server then sends the received data to a generative model, which verbalizes it specifically as "maternity harassment, a case where a woman is excluded from promotions or work because of pregnancy." The verbalized data is saved in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is saved on the server, and the progress of problem-solving is regularly updated.

[0964] The above is a specific description of an embodiment of the present invention. This system allows for quick verbalization and recognition of issues, and promotes investment and solutions by communities and individuals.

[0965] The processing flow will be explained below.

[0966] Step 1:

[0967] A user logs in to the system's web page or application using a device (smartphone or PC).

[0968] Step 2:

[0969] Users click the "Post a new social issue" button to access a new entry form, where they can enter the social issues or personal suffering they are facing in the text area.

[0970] Step 3:

[0971] When the user completes the input, they press the "Submit" button, which converts the input data into JSON format data on the device.

[0972] Step 4:

[0973] The device sends this JSON format data to the server using the HTTPS protocol, after which a message indicating successful data transmission is displayed to the user.

[0974] Step 5:

[0975] The server analyzes the received JSON data and extracts necessary fields (user ID, details of the social issue, etc.), and prepares the extracted data for passing to the generative model.

[0976] Step 6:

[0977] The server calls the API of the generative model (such as ChatGPT) and sends the analyzed data. Based on the received data, the generative model verbalizes the social issues in appropriate terms.

[0978] Step 7:

[0979] The generative model returns the verbalized data to the server, for example, "Pregnant employees are harassed at work and excluded from promotions and jobs."

[0980] Step 8:

[0981] The server receives the verbalized data and stores it in the database, logging the success of the save.

[0982] Step 9:

[0983] The server then formats the stored data for public viewing and displays it on a special web page or application, making the information accessible to other users.

[0984] Step 10:

[0985] Users can click the "Sympathize" button for a published issue, or if they want to enter a comment or provide specific support, they can click the "Invest" button and enter the required information.

[0986] Step 11:

[0987] The device converts data related to sympathy and investment into JSON format and sends it back to the server via HTTPS protocol.

[0988] Step 12:

[0989] The server receives the empathy data and the contribution data and stores them in a database. Once the contribution information is saved, a thank you message is sent to the user.

[0990] Step 13:

[0991] The server periodically updates the progress of the problem and displays it on a web page or application, allowing users to check the progress.

[0992] Step 14:

[0993] Users can use a dedicated dashboard to check the progress and new information on the projects they have funded in real time.

[0994] Step 15:

[0995] The server periodically notifies the contributor of the progress by email. This notification is sent automatically according to the timing of updates to the progress status within the system.

[0996] This is the specific processing flow of this system, which enables appropriate verbalization and rapid recognition of social issues, as well as promoting investment and solutions by communities and individuals.

[0997] Example 1

[0998] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0999] In conventional systems, it was difficult for users to quickly and appropriately verbalize the personal or social challenges they faced and to solicit sympathy and investment from other users. In addition, there was a lack of visualization of the progress of the challenges and information provided to investors, making it difficult to provide support for problem-solving efficiently.

[1000] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1001] In this invention, the server includes a means for receiving task data entered by a user, a means for converting the task data into JSON format, and a means for transmitting the converted JSON format data via HTTPS, thereby enabling the task data entered by a user to be quickly and appropriately transmitted to the server for analysis and verbalization.

[1002] "User" refers to an individual or corporation that uses this system to input issue data and sympathize with or invest in the project.

[1003] "Issue data" refers to information entered in text format about social issues or personal problems that users are facing.

[1004] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight text data format that represents data in a structured manner.

[1005] "HTTPS protocol" stands for HyperText Transfer Protocol Secure and refers to an internet protocol for secure communication.

[1006] A "generative AI model" refers to an artificial intelligence model that uses natural language processing to analyze input data and convert it into an appropriate language.

[1007] A "database" refers to a system for organizing and storing information, and for efficiently searching, retrieving, and updating information as needed.

[1008] "Publication format" refers to a format in which data has been converted into a form that can be viewed by other users, such as HTML or JSON.

[1009] "Empathy" refers to the act of users expressing emotional reactions to published assignment data and sending feedback.

[1010] "Investment" refers to the act of a user providing their own resources (time, money, skills, etc.) to solve a problem.

[1011] A "staging area" refers to an area where received data is temporarily stored and its format and content are validated.

[1012] "Validation" refers to the process of checking whether the content of data is accurate and valid.

[1013] "Dedicated form" refers to a special input screen provided within the system for users to input assignment data.

[1014] The "thank you message" refers to a message sent from the server to the user who made the investment, expressing gratitude.

[1015] A "dashboard" refers to a visual interface that allows users to check the progress of problem-solving in real time.

[1016] A "scheduler" refers to a program that executes a specific process at a fixed time.

[1017] This invention is a system that operates in cooperation with the user, the terminal, and the server. Specifically, it quickly analyzes the problem data entered by the user, properly verbalizes it, and then publishes it, thereby streamlining the process of soliciting sympathy and investment.

[1018] System Configuration

[1019] User Input

[1020] Users access the system using a device (smartphone or PC). They can enter the social issues and personal suffering they are facing in text format through a dedicated web page or application. This input is saved at regular intervals using an auto-save function. After completing the input, the user clicks the send button, and the data is converted into JSON format and sent to the server using the HTTPS protocol.

[1021] Sending and Receiving Data

[1022] The terminal converts the data entered by the user into JSON format and sends it to the server via the HTTPS protocol. The server temporarily stores the received data in a staging area and validates the data to ensure that its format and content are appropriate.

[1023] Data analysis and verbalization

[1024] The server formats the JSON data stored in the staging area so that it can be used by a generative AI model (e.g., ChatGPT). This formatted data is passed to the generative model, which analyzes the data and verbalizes the problem. For example, if an input is "I am being harassed at work because I am pregnant," the generative model verbalizes this as "An example of maternity harassment is being excluded from promotions or work because of pregnancy."

[1025] Storing and publishing verbalized data

[1026] The server stores the verbalized data returned by the generative model in a database. This stored data can then be converted into a publicly available format (e.g., HTML or JSON) and displayed on a dedicated web page or application. This process allows other users to access and view this information.

[1027] Seeking sympathy and investment

[1028] Other users can express their "sympathy" for the published challenge. Users who want to express their sympathy click the "Sympathy" button, and their feedback is sent from their device to the server. Users can also click the "Invest" button and enter details of their resources, such as time, money, or skills, into a dedicated form. This information is also sent from their device to the server.

[1029] Management of investment information

[1030] The terminal converts the user's contribution information into JSON format and sends it to the server via HTTPS. After receiving the contribution information, the server validates it and stores it in the database. After the contribution is completed, a thank-you message is sent to the user.

[1031] Progress feedback

[1032] The server periodically updates the progress of the problem-solving process. This progress information is retrieved from the database and displayed on a dedicated web page or application. Users who have contributed or sympathized with the project are also notified of the progress via email. A system is also provided that allows users to check progress information in real time via a dedicated dashboard.

[1033] Prompt Sentence Examples

[1034] Please explain in detail the harassment you have experienced in the workplace.

[1035] The above is a specific embodiment of the present invention, which enables a user to quickly and appropriately verbalize the issues they face and solicit sympathy and investment from other users.

[1036] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1037] Step 1:

[1038] Users log in to the system using their own device (smartphone or PC). They enter the social issues and personal suffering they are facing in text format into a dedicated form. The input information is automatically saved at regular intervals. Once the input is complete, the user clicks the send button.

[1039] Input: User-entered assignment data (text format)

[1040] Output: Send instructions are generated on the user's terminal

[1041] Step 2:

[1042] The terminal receives the task data entered by the user, converts it into JSON format, and sends the converted data to the server using the HTTPS protocol.

[1043] Input: User-entered assignment data (text format)

[1044] Data processing: Converting issue data into JSON format

[1045] Output: JSON format data is sent to the server

[1046] Step 3:

[1047] The server temporarily stores the JSON data received via HTTPS in a staging area, where the format and content of the data are validated.

[1048] Input: Issue data in JSON format

[1049] Data processing: Validating the format and content of JSON data

[1050] Output: Pass validated JSON data to the generated AI model

[1051] Step 4:

[1052] The server passes the validated JSON data to a generative AI model (e.g., ChatGPT), which analyzes and verbalizes the data. The generative model then organizes the input data into appropriate terms and converts them into specific social issues. For example, if an input states, "I am being harassed at work because I am pregnant," the generative model verbalizes this as, "An example of maternity harassment is being excluded from promotions or jobs at work because of pregnancy."

[1053] Input: Validated JSON data

[1054] Data Computation: Data Analysis and Verbalization with Generative AI Models

[1055] Output: Verbalized task data

[1056] Step 5:

[1057] The server stores the verbalized data returned by the generative AI model in a database, converts the stored data into a publicly available format (e.g., HTML, JSON), and displays it on a dedicated webpage or application.

[1058] Input: Verbalized task data

[1059] Data processing: converting data into a format for publication

[1060] Output: Data displayed on a dedicated web page or application

[1061] Step 6:

[1062] Other users can express their sympathy for the published problem data. By clicking the "Sympathize" button, feedback is sent from the device to the server. Users can also click the "Invest" button and enter details of their resources, such as time, money, or skills, into a dedicated form. This information is also sent from the device to the server.

[1063] Input: The like or pledge button the user clicked

[1064] Data processing: Sending feedback or contribution information

[1065] Output: Empathy or pledge data sent to the server

[1066] Step 7:

[1067] The server receives the sympathy and contribution data, validates the contents, and stores them in the database. After the contribution is completed, a thank you message is sent to the user.

[1068] Input: Empathy data, investment data

[1069] Data processing: validation and saving to database

[1070] Output: Validated empathy data, pledge data, and a thank you message

[1071] Step 8:

[1072] The server periodically updates the progress of the project. This progress information is retrieved from the database and displayed on a dedicated web page or application. Users who have contributed or sympathized are notified of the progress by email, and can check the progress information in real time through a dedicated dashboard.

[1073] Input: Progress information in the database

[1074] Data processing: Updating and obtaining progress information

[1075] Output: Publishing and notifying progress updates

[1076] (Application example 1)

[1077] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1078] Conventional problem-solving systems lacked sufficient means for users to quickly verbalize the social issues and personal suffering they faced and then share that information widely. Furthermore, they lacked a means to create advertisements based on verbalized problem data and efficiently solicit sympathy and investment, making it difficult to effectively gather support for problem-solving. For this reason, a new system was needed to quickly and effectively solve users' problems across society.

[1079] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1080] In this invention, the server includes means for transmitting problem data entered by the user to a generative model for analysis and verbalization, means for embedding the generated verbalized data in an advertising template to generate an advertisement, and means for distributing the generated advertisement to social media and websites. This makes it possible to quickly share users' problems and generate advertisements based on them to effectively attract sympathy and investment.

[1081] A "user" is an individual or organization that inputs assignment data and shares that assignment through the system.

[1082] "Issue data" is text data that expresses the social issues and personal suffering that users are facing.

[1083] A "generative model" is an artificial intelligence model that analyzes input task data and converts it into appropriate words.

[1084] "Verbalized data" is task data that has been analyzed by a generative model and converted into an appropriate format.

[1085] An "advertising template" is a model of an advertisement prepared for embedding generated verbalized data.

[1086] "Advertising" refers to content generated based on verbalized data and distributed on social media and websites.

[1087] "Social media" is a general term for online platforms through which users receive advertising.

[1088] A "Website" is an online page for displaying advertisements on the Internet.

[1089] "Empathy" is an act in which other users show emotional understanding and support for a published issue.

[1090] "Contribution" is the act of a user providing resources such as time, money, or skills to a published challenge.

[1091] "Progress information" is data that indicates the progress of problem solving and the current situation.

[1092] "Advertising status management" is the process of monitoring and controlling the status of advertising on social media and websites.

[1093] This invention is a system that allows users to quickly verbalize social issues and personal suffering they are facing and share it widely. This system aims to effectively attract sympathy and investment by creating advertisements based on the generated verbalization data through collaboration between users, devices, generative models, and servers.

[1094] System Overview

[1095] 1. User input:

[1096] Users access the system using devices such as smartphones or PCs. A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. The text entered in this form is treated as assignment data.

[1097] 2. Receiving and sending assignment data:

[1098] The terminal receives the assignment data entered by the user, converts it into JSON format, and then sends the converted data to the server using the HTTPS protocol.

[1099] 3. Data analysis and verbalization:

[1100] The server passes the received JSON data to a generative model (such as ChatGPT) to analyze and verbalize the data. The generative model then organizes and converts the problem data into appropriate language, converting it into specific social issues.

[1101] 4. Ad generation and delivery:

[1102] The server embeds the generated verbalized data into an advertising template, which generates an advertisement designed to resonate with users. The generated advertisement is then distributed to social media and websites. The server also collects and analyzes user feedback on the advertisement to evaluate its effectiveness.

[1103] 5. Empathy and stake management:

[1104] Other users can express their sympathy for the published issues. Data on sympathy and contributions is also sent to the server and stored in a database. The server periodically updates the progress of the issue and notifies the contributors and other stakeholders by email.

[1105] Specific examples

[1106] For example, User A inputs her experience of "being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server then sends this data to a generative model, which verbalizes it specifically as "problems related to maternity harassment in the workplace." The verbalized data is embedded in an ad template, and an ad is automatically generated that reads, "(Relatable ad) Problem: Maternity harassment is occurring in the workplace. We need your support. Learn more: www.example.com / donate." This ad is then distributed on social media and websites, and feedback is collected.

[1107] Prompt Sentence Examples

[1108] An example of an input prompt for a generative AI model is as follows:

[1109] "Verbalize the following user input for advertising: I am being harassed at work because I am pregnant"

[1110] The above description provides a detailed explanation of how the present invention can be implemented, allowing users to quickly articulate the challenges they face and gain widespread sympathy and investment.

[1111] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1112] Step 1:

[1113] Users access a dedicated web page or application using a device such as a smartphone or PC and input their experiences and thoughts. The input data is treated as assignment data. In this case, the text data entered by the user becomes input data to be passed on to the next processing step.

[1114] Step 2:

[1115] The terminal receives the assignment data entered by the user and converts it into JSON format. The converted data is sent to the server using the HTTPS protocol. Here, the input is the assignment data and the output is JSON format data.

[1116] Step 3:

[1117] The server passes the received JSON data to a generative model, which analyzes and verbalizes the data. The generative model (such as ChatGPT) organizes and converts the task data into appropriate language. The input for this process is JSON data, and the output is verbalized data. Specific data processing involves analyzing the task data and converting it into appropriate language expressions.

[1118] Step 4:

[1119] The server embeds the generated verbalized data into an advertising template. The advertising template is a pre-prepared format, and specific advertising content is generated by embedding the verbalized data. The inputs to this process are the verbalized data and the advertising template, and the output is the generated advertisement. Specifically, the verbalized data is inserted into a placeholder in the template.

[1120] Step 5:

[1121] The server distributes the generated advertisements to social media platforms and websites. After the advertisements are distributed, users can provide feedback on the advertisements. The input of this process is the generated advertisement, and the output is the distributed advertisement and user feedback. Specifically, the advertisements are sent to social media APIs and the website's advertisement management system.

[1122] Step 6:

[1123] The server collects and analyzes user responses to advertisements from social media and websites. The effectiveness of the advertisements is evaluated based on the collected feedback data. The input to this process is the feedback data, and the output is the analysis results. Specifically, the feedback data is stored in a database and statistical analysis and text mining are performed.

[1124] Step 7:

[1125] Other users can express their support or investment in the published issues. The server also receives this data and stores it in a database. Based on the support and investment data, progress information on the issue resolution is generated, updated periodically, and notified to investors and related parties via email. The input to this process is support and investment data, and the output is progress information and notification emails. Specifically, the support and investment data is analyzed, progress information is generated, and notifications are sent using the email system.

[1126] The above are the specific processing steps of the system program that realizes the application example.

[1127] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1128] This invention is a system that aims to quickly verbalize the social issues and personal suffering faced by users, and to widely solicit sympathy and investment. This system is based on collaboration between a server, a device, and a user, and is characterized by its ability to appropriately verbalize issues using a generative model. In addition, by combining it with an emotion engine that recognizes the user's emotions, it enables more accurate analysis and more effective motivation for sympathy and investment.

[1129] System Overview

[1130] 1. User Input

[1131] Users access the system using a device (smartphone or PC). A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. Here, users enter text about the social issues and personal suffering they are facing. Once they have finished entering the text, they press the send button.

[1132] 2. Sending and Receiving Input Data

[1133] The terminal receives the data entered by the user, converts it to JSON format, and then sends the converted data using the HTTPS protocol to the server, which receives the data and prepares it for analysis.

[1134] 3. Emotion Data Recognition and Analysis

[1135] The server applies an emotion engine to the received JSON data to analyze the user's emotions. For example, it extracts emotions (happiness, sadness, anger, etc.) from the text data and generates an emotion score.

[1136] 4. Data analysis and verbalization

[1137] Taking the analyzed emotion data into consideration, the server passes the received JSON data to a generative model (such as ChatGPT) for data analysis and verbalization. The generative model then organizes the problem data into appropriate terms and converts it into a specific social issue. For example, a statement such as "A pregnant employee was harassed at work and excluded from promotions and work" can be verbalized as "An example of maternity harassment is being excluded from promotions and work due to pregnancy."

[1138] 5. Preservation and publication of verbalized data

[1139] The server stores the verbalized and emotional data returned by the generative model in a database, which then converts the data into a publicly available format and displays it on a dedicated web page or application, allowing other users to access and view the information.

[1140] 6. Seeking sympathy and investment

[1141] Other users can sympathize with the published challenge. By clicking the "Sympathize" button, users can send their feedback to the system. If users want to contribute their resources (time, money, skills, etc.) to the challenge, they can click the "Contribute" button and fill in the appropriate form.

[1142] 7. Management of investment information

[1143] The terminal sends the user's contribution information to the server. The server receives this information and stores it in a database. Once the contribution information is registered, a thank-you message is sent to the user.

[1144] 8. Progress Feedback

[1145] The server periodically updates the progress of the problem-solving process and displays it on a special webpage and application. Users who have invested or sympathized with the project will be notified of the progress by email. A dedicated dashboard will also be provided, allowing users to check detailed progress information in real time.

[1146] Specific examples

[1147] User A inputs and submits her "experience of workplace harassment due to pregnancy." This data is converted to JSON format and sent to the server via HTTPS protocol. The server analyzes the received data through an emotion engine and generates an emotion score. This is then sent to the generative model along with the analyzed emotion data, which is then specifically verbalized as "maternity harassment, a case where a woman is excluded from promotions or work due to pregnancy." The verbalized data and emotion data are stored in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is stored on the server, and the progress of problem-solving is regularly updated.

[1148] The above is a specific description of an embodiment of the present invention. This system enables quick verbalization and recognition of issues, and promotes investment and solutions by communities and individuals. Furthermore, by recognizing the user's emotions, it is possible to empathize more effectively and motivate investment.

[1149] The processing flow will be explained below.

[1150] Step 1:

[1151] A user logs in to the system's web page or application using a device (smartphone or PC).

[1152] Step 2:

[1153] The user clicks the "Post a new social issue" button to access a new entry form. Here, the user enters the social issue or personal suffering they are facing into the text area. For example, the user could provide details such as "I was harassed at work because I am pregnant."

[1154] Step 3:

[1155] When the user completes the input, they press the "Submit" button, which converts the input data into JSON format data on the device.

[1156] Step 4:

[1157] The device sends this JSON format data to the server using the HTTPS protocol, after which a message indicating successful data transmission is displayed to the user.

[1158] Step 5:

[1159] The server analyzes the received JSON data and extracts necessary fields (user ID, details of the social issue, etc.), and prepares the extracted data for passing to the generative model.

[1160] Step 6:

[1161] The server sends the task data to the emotion engine, which extracts emotions from the text data and generates an emotion score (e.g., a range from 0 to 1 representing joy, sadness, anger, etc.).

[1162] Step 7:

[1163] The analyzed data, along with the emotion score generated by the server, is sent to a generative model (e.g., ChatGPT) for analysis and verbalization. The generative model then organizes the issue data into concrete terms and converts it into a social issue. For example, "I was harassed at work because I was pregnant" is verbalized as "An example of maternity harassment is when a woman is excluded from promotions or jobs at work because she is pregnant."

[1164] Step 8:

[1165] The server saves the verbalized data and sentiment scores returned by the generative model to a database, and logs the success of the save.

[1166] Step 9:

[1167] The server then formats the stored data for public viewing and displays it on a special web page or application, making the information accessible to other users.

[1168] Step 10:

[1169] Users can click the "Sympathize" button for a published issue, or if they want to enter a comment or provide specific support, they can click the "Invest" button and enter the required information.

[1170] Step 11:

[1171] The device converts data related to sympathy and investment into JSON format and sends it back to the server via HTTPS protocol.

[1172] Step 12:

[1173] The server receives the empathy data and the contribution data and stores them in a database. Once the contribution information is saved, a thank you message is sent to the user.

[1174] Step 13:

[1175] The server periodically updates the progress of the problem and displays it on a web page or application, allowing users to check the progress.

[1176] Step 14:

[1177] Users can use a dedicated dashboard to check the progress and new information on the projects they have funded in real time.

[1178] Step 15:

[1179] The server periodically notifies the contributor of the progress by email. This notification is sent automatically according to the timing of updates to the progress status within the system.

[1180] As a concrete example, User A inputs and submits "an experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server analyzes the received data using an emotion engine to generate an emotion score. This is then sent to the generative model along with the analyzed emotion data, which is specifically verbalized as "maternity harassment, a case where a woman is excluded from promotions or work because of pregnancy." The verbalized data and emotion data are stored in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and makes an additional investment of 1,000 yen. This information is stored on the server, and the progress of problem-solving is regularly updated.

[1181] The above is the specific processing flow of this system. This enables appropriate verbalization and rapid recognition of social issues, as well as promoting investment and solutions by communities and individuals. Furthermore, the introduction of an emotion engine enables analysis that takes into account the user's emotions and expands empathy.

[1182] Example 2

[1183] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1184] In modern society, there is a lack of ways for individuals to quickly verbalize the social issues and personal suffering they face and to solicit widespread sympathy and investment. As a result, individual problems are not easily recognized by society, and it takes a long time to receive effective support. Furthermore, the lack of a system that can appropriately handle users' emotions means that there is insufficient motivation for empathy and investment.

[1185] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1186] In this invention, the server includes means for receiving task data entered by a user, means for converting the received task data into JSON format, means for transmitting the converted data via HTTPS, means for analyzing the task data and generating an emotional score, means for transmitting the analyzed emotional score and task data to a generative AI model for analysis and verbalization, means for saving the verbalized task data in a database, means for generating and publishing the saved task data for display, means for accepting sympathy and contributions for the published task data, means for receiving and saving the sympathy and contribution data, and means for generating, publishing, and notifying progress information on problem solving. This enables rapid verbalization and widespread sharing of task data and motivates sympathy and contributions.

[1187] "User" refers to any individual or entity that uses the System.

[1188] "Issue data" refers to text data entered by users about social issues or personal suffering.

[1189] "JSON format" refers to a JavaScript Object Notation data structure, a text format used for exchanging and storing data.

[1190] The "HTTPS protocol" is a communication protocol for securely transferring data over the Internet.

[1191] "Emotion score" refers to a numerical representation of the type and intensity of emotions extracted from text data.

[1192] A "generative AI model" refers to an artificial intelligence algorithm that uses a large-scale language model to parse and verbalize data.

[1193] A "database" refers to a system for efficiently storing, managing, and searching large amounts of data.

[1194] "Publication" refers to making the stored data publicly available for viewing via the Internet.

[1195] "Empathy" refers to the act of other users showing sympathy or understanding for a published issue.

[1196] "Contribution" refers to the act of other users providing resources (funds, time, skills, etc.) to a published challenge.

[1197] "Thank you message" refers to a message of gratitude sent from the server when a user makes a contribution.

[1198] "Progress information" refers to data regarding the progress of activities toward resolving a problem.

[1199] A "dashboard" refers to an interface designed to allow users to see the status and progress of a system at a glance.

[1200] This invention is a system that aims to quickly verbalize the social issues and personal suffering faced by users, and to widely solicit sympathy and investment. The system is based on three-way collaboration between a server, a terminal, and a user. This enables the appropriate verbalization of issues using a generative AI model, combined with an emotion engine that recognizes the user's emotions, enabling more accurate analysis and effective motivation for sympathy and investment. The specific hardware and software used will be explained in turn.

[1201] First, the user accesses the system using a terminal. The terminal can be a smartphone or personal computer, and a form is provided for the user to enter their experiences and thoughts. The user enters the assignment data through a dedicated web page or application and presses the submit button.

[1202] The device receives the text data entered by the user and converts it into JSON format. It then sends it to the server using the HTTPS protocol. The server prepares the received JSON data for analysis. Specifically, the server uses an emotion engine (e.g., IBM Watson or Google Cloud Natural Language API) to analyze the user's emotions. This process extracts emotions such as joy, sadness, and anger from the entered text data and generates an emotion score.

[1203] The server then passes the analyzed emotion data and issue data to a generative AI model (such as ChatGPT). The generative AI model then organizes the given issue data into appropriate language and converts it into a specific social issue. For example, a statement such as "A pregnant employee was harassed at work and excluded from promotions and work" can be verbalized as "Maternity harassment involves being excluded from promotions and work due to pregnancy."

[1204] The server stores the verbalized data in a database, converts the data into a public format, and instantly publishes it on a special web page or application, allowing other users to view the information.

[1205] Other users can show their support or investment in the published challenge. By clicking the "Support" button, users can send feedback to the system. Also, by clicking the "Invest" button, users who want to donate their resources (time, money, skills, etc.) can fill out the appropriate form and send it from their device to the server. The server stores the received investment information in a database and manages it.

[1206] Furthermore, the server periodically updates the progress of the project and displays it on a special webpage or application. Users who sympathize or invest in the project will be notified of the progress by email. Users can check detailed progress information in real time via a dedicated dashboard.

[1207] Examples:

[1208] User A inputs and submits her "experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server analyzes the received data using an emotion engine to generate an emotion score. This is then sent to a generative model along with the analyzed emotion data, which is then specifically verbalized as "maternity harassment, being excluded from promotions or work because of pregnancy." The verbalized data and emotion data are saved in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is saved on the server, and progress in solving the problem is regularly updated.

[1209] Example prompt sentence:

[1210] "I feel that I have been harassed at work because I am pregnant. Based on this experience, please appropriately articulate what kind of social issue this is."

[1211] The above is a specific embodiment of the present invention. A system is constructed that recognizes the user's emotions at each processing step and provides appropriate empathy and motivation for investment.

[1212] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1213] Step 1:

[1214] User Input

[1215] Users access the system using a device (smartphone or PC). They enter text about the social issues they face or their personal suffering into an input form on a dedicated webpage or application, and click the submit button. For example, a user might enter "My experience of being harassed at work because of my pregnancy." The input data is sent to the device in text format.

[1216] Input: Text data entered by the user

[1217] Output: Text data is saved to the device.

[1218] Step 2:

[1219] Sending and Receiving Input Data

[1220] The terminal converts the text data entered by the user into JSON format using a JSON encoder running on the terminal, and then sends the converted data to the server using the HTTPS protocol. The server checks the integrity of the received JSON data and prepares it for parsing.

[1221] Input: Text data

[1222] Output: JSON format data

[1223] Specific behavior:

[1224] The device encodes the text data into JSON format.

[1225] The converted JSON data is sent to the server via HTTPS protocol.

[1226] The server verifies the integrity of the data received.

[1227] Step 3:

[1228] Emotional Data Recognition and Analysis

[1229] The server passes the received JSON data to an emotion engine (e.g., IBM Watson or Google Cloud Natural Language API) to analyze the user's emotions. This analysis process extracts emotions (happiness, sadness, anger, etc.) from the text data and generates an emotion score. The server receives the generated emotion score and prepares it for the next step.

[1230] Input: JSON format data

[1231] Output: Sentiment score

[1232] Specific behavior:

[1233] The server passes the JSON data to the emotion engine.

[1234] The emotion engine extracts emotions from the text data and generates an emotion score.

[1235] A server receives the emotion scores from the emotion engine.

[1236] Step 4:

[1237] Data analysis and verbalization

[1238] The server passes the emotion score and analyzed JSON data to a generative AI model (e.g., ChatGPT). The generative AI model then organizes the input issue data into appropriate terms and converts them into specific social issues. For example, "experiences of workplace harassment due to pregnancy" can be verbalized as "maternity harassment, being excluded from promotions or work due to pregnancy."

[1239] Input: sentiment scores, parsed JSON data

[1240] Output: Verbalized text data

[1241] Specific behavior:

[1242] The server sends the sentiment scores and parsed JSON data to the generative AI model.

[1243] The generative AI model organizes the information into appropriate words and verbalizes it as a specific social issue.

[1244] The server receives the verbalized data.

[1245] Step 5:

[1246] Storing and publishing verbalized data

[1247] The server stores the verbalized text data returned by the generative model in a database, converts it into a publicly available format, and displays it on a dedicated web page or application, allowing other users to access and view the information.

[1248] Input: Verbalized text data

[1249] Output: Public data displayed on a dedicated web page or application

[1250] Specific behavior:

[1251] The server stores the verbalized data in a database.

[1252] Convert the stored data into a publishing format (e.g. HTML, JSON).

[1253] The published data will be displayed on special web pages and applications.

[1254] Step 6:

[1255] Seeking sympathy and investment

[1256] Other users can show their support or contribution to the published issue. Users click the "Support" button to send feedback, or click the "Contribute" button to fill out a form and send it to the server from their device. The server processes the received support and contribution data.

[1257] Input: User sympathy and investment information

[1258] Output: Sympathy and pledge data stored on the server

[1259] Specific behavior:

[1260] A user views the public data and clicks the sympathy or contribution button.

[1261] Enter your sympathy and investment information and send it from your device to the server.

[1262] The server stores the received data in a database.

[1263] Step 7:

[1264] Management of investment information

[1265] The terminal sends the contribution information entered by the user to the server. The server receives this information and stores it in a database. After confirming that the contribution information has been successfully saved, a thank-you message is sent to the user.

[1266] Input: Investment information

[1267] Output: Contribution information stored in the database, a thank you message

[1268] Specific behavior:

[1269] The terminal transmits the user's contribution information to the server.

[1270] The server stores the investment information in a database.

[1271] Send a thank you message to the user.

[1272] Step 8:

[1273] Progress feedback

[1274] The server periodically updates the progress of the project and displays it on a special webpage and application. Users who sympathize with or invest in the project are notified of the progress by email. Users can also check detailed progress information in real time via a dedicated dashboard.

[1275] Input: Progress information

[1276] Output: Progress information displayed on a dedicated web page or in the application, notification emails sent to users

[1277] Specific behavior:

[1278] The server updates the progress of the issue resolution.

[1279] Display it on a special web page or application.

[1280] Users who have sympathized or invested will be notified of progress via email.

[1281] Users can view progress information on a dedicated dashboard.

[1282] (Application example 2)

[1283] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1284] Previous systems lacked the means to quickly and appropriately verbalize the social challenges and personal suffering they faced and share those experiences with other users. Furthermore, the lack of specific methods for soliciting sympathy and investment, and the lack of clear feedback on progress, weakened users' motivation to solve the problems. Furthermore, the lack of a mechanism for properly recognizing users' emotions made effective analysis difficult.

[1285] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving task data entered by a user, means for transmitting the task data to a generative model and analyzing and verbalizing it, means for saving the verbalized task data in a database, means for generating and publishing the saved task data for display, means for accepting sympathy and contributions for the published task data, means for receiving and saving the sympathy and contribution data, means for generating, publishing, and notifying task-solving progress information, means for receiving task data entered by a user from a smartphone application, and means for generating emotion data by applying the generated data to an emotion analysis engine. This allows the task data entered by a user to be quickly and appropriately verbalized and shared with many users, making it easier to solicit sympathy and contributions and enabling timely feedback on the progress of task solving.

[1286] "User-entered problem data" is text information that describes the social problems and personal difficulties that the user is facing.

[1287] A "generative model" is a model that uses artificial intelligence to analyze input data and appropriately verbalize it in natural language.

[1288] An "emotion analysis engine" is software that analyzes a user's emotions from input text and generates emotional data.

[1289] The "database" is a data storage system for storing and managing verbalized issue data and empathy / investment data.

[1290] "Sympathy and investment" refers to the act of a user emotionally supporting a published issue and providing funds or resources.

[1291] "Progress information" is data that indicates the current status and progress of efforts to solve a problem.

[1292] A "web page" is a page for displaying information that is published on the Internet and can be viewed by users.

[1293] A "dashboard" is an interface that allows users to visually check their progress.

[1294] A "smartphone application" is a software application that runs on a smartphone and is a means by which a user inputs and transmits assignment data.

[1295] The "HTTPS protocol" is an internet protocol for securely transmitting data.

[1296] This invention is a system that allows users to quickly verbalize the social issues and personal suffering they are facing, and solicit sympathy and investment from other users. This system is realized through cooperation between a server, a terminal, and a user.

[1297] 1. User Input

[1298] Users access the system using a smartphone application and input their own problem data, which may include social issues or personal difficulties, such as experiencing harassment at work because of pregnancy. The input data is then sent from the smartphone application to the server.

[1299] 2. Sending and Receiving Data

[1300] The terminal converts the task data entered by the user into JSON format and sends it to the server using the HTTPS protocol. The server prepares the received task data for analysis.

[1301] 3. Emotion analysis and verbalization

[1302] The server runs the received task data through an emotion analysis engine to analyze the user's emotions. For example, emotions such as sadness or anger are extracted from the text and emotion data is generated. The emotion-analyzed data and task data are then sent to a generative AI model, which then translates the data into appropriate language.

[1303] 4. Preservation and publication of verbalized data

[1304] The server stores the verbalized data returned by the generative AI model in a database, which then publishes the data in real time on a special webpage.

[1305] 5. Accepting sympathy and investment

[1306] Other users can express their sympathy for the issue data published on the web page. If they want to donate resources such as time, money, or skills, they can click the contribution button and fill in the appropriate form. This sympathy and contribution data is received by the server and stored in a database.

[1307] 6. Progress Feedback

[1308] The server will periodically update the progress of the project and make it available to users via a special webpage and a dedicated dashboard. Users who have contributed will also be notified of the progress via email.

[1309] Hardware and software used

[1310] Hardware: Smartphone, Server (e.g. AWS, GCP)

[1311] Software: Python, Hugging Face Transformers, OpenAI GPT-3

[1312] At each step of this system, the user's input data is analyzed and verbalized appropriately through a sentiment analysis engine and a generative AI model, and then published in real time, enabling other users to sympathize with and contribute. As a concrete example, let's use the following prompt sentence.

[1313] Prompt Sentence Examples

[1314] Social Issue: Harassment at Work Because of Pregnancy

[1315] Emotion: [{'label': 'Sad', 'score': 0.95}]

[1316] To put this in words:

[1317] This allows the problem data entered by users to be quickly and appropriately verbalized and shared with many users.The system promotes awareness of problems and functions as a platform for soliciting sympathy and investment to create more effective solutions.

[1318] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1319] Step 1:

[1320] The user starts the smartphone application and inputs their assignment data. For example, the user may enter text about their experience of being harassed at work because of pregnancy. This input data is temporarily saved by the smartphone application.

[1321] input:

[1322] Assignment text (e.g., "I was harassed at work because I was pregnant.")

[1323] output:

[1324] Temporarily saved text data

[1325] Step 2:

[1326] The terminal converts the saved text data into JSON format and sends it to the server using the HTTPS protocol. The converted JSON data contains the text content.

[1327] input:

[1328] Temporarily saved text data

[1329] Data processing:

[1330] Convert text data to JSON format

[1331] output:

[1332] Issue data in JSON format

[1333] Step 3:

[1334] The server receives the assignment data in JSON format sent from the device, and temporarily stores the received data in preparation for analysis.

[1335] input:

[1336] Issue data in JSON format

[1337] output:

[1338] Temporarily saved JSON format issue data

[1339] Step 4:

[1340] The server runs the received task data through a sentiment analysis engine to analyze the user's emotions. The sentiment analysis engine extracts emotions (happiness, sadness, anger, etc.) from the text and generates an emotion score. For example, the emotion "sad" and its score are extracted.

[1341] input:

[1342] Issue data in JSON format

[1343] Data Calculation:

[1344] Sentiment extraction and scoring through text analysis

[1345] output:

[1346] Emotion data (e.g., sad 0.95)

[1347] Step 5:

[1348] The server sends the analyzed emotion data and issue data to the generative AI model, which then verbalizes them appropriately. The generative AI model then organizes the issue data and verbalizes it as a specific social issue. For example, "an experience of being harassed at work because of pregnancy" is verbalized as "an example of maternity harassment is being excluded from promotions or work because of pregnancy."

[1349] input:

[1350] Emotion data and issue data

[1351] Data Calculation:

[1352] Verbalization using generative AI models

[1353] output:

[1354] Verbalized problem data

[1355] Step 6:

[1356] The server stores the verbalized assignment data in a database, after which the assignment data is made public in real time on a special web page.

[1357] input:

[1358] Verbalized problem data

[1359] output:

[1360] Data stored in the database, published assignment data

[1361] Step 7:

[1362] Users can view the issue data published on the webpage and sympathize or contribute. To sympathize, click the "Sympathize" button, and to contribute, click the "Contribute" button and enter the necessary information in the appropriate form. This generates sympathy and contribution data.

[1363] input:

[1364] Published assignment data

[1365] output:

[1366] Empathy or sponsorship data

[1367] Step 8:

[1368] The server receives the empathy and contribution data and stores it in a database. After storing it, the progress of the problem solving is updated and notified to the user.

[1369] input:

[1370] Empathy and investment data

[1371] output:

[1372] Sympathy and investment data stored in database, progress notifications

[1373] Step 9:

[1374] The server will periodically update the progress of the project and make it available to users via a special webpage and a dedicated dashboard. Users who have contributed will also be notified of the progress via email.

[1375] input:

[1376] Progress Information

[1377] output:

[1378] Progress updates, notification emails

[1379] The above are the specific processing steps of the system that realizes the application example.

[1380] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1381] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1382] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1383] [Fourth embodiment]

[1384] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1385] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1386] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1387] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1388] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1389] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1390] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1391] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1392] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1393] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1394] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1395] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1396] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1397] This invention is a system that aims to quickly verbalize the social issues and personal suffering that users are facing, and to widely solicit sympathy and investment. This system is based on cooperation between a server, a terminal, and a user, and is characterized by its ability to appropriately verbalize issues using a generative model.

[1398] System Overview

[1399] 1. User Input

[1400] Users access the system using a device (smartphone or PC). A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. Here, users enter text about the social issues and personal suffering they are facing. Once they have finished entering the text, they press the send button.

[1401] 2. Sending and Receiving Input Data

[1402] The terminal receives the data entered by the user, converts it to JSON format, and then sends the converted data using the HTTPS protocol to the server, which receives the data and prepares it for analysis.

[1403] 3. Data analysis and verbalization

[1404] The server passes the received JSON data to a generative model (such as ChatGPT), which analyzes and verbalizes the data. The generative model then organizes the problem data into appropriate terms and converts it into specific social issues. For example, if the content includes "I am being harassed at work because I am pregnant," this can be verbalized as "An example of maternity harassment is being excluded from promotions or jobs at work because of pregnancy."

[1405] 4. Preservation and publication of verbalized data

[1406] The server stores the verbalized data returned by the generative model in a database, which then converts it into a publicly available format and displays it on a dedicated web page or application, allowing other users to access and view this information.

[1407] 5. Seeking sympathy and investment

[1408] Other users can sympathize with the published challenge. By clicking the "Sympathize" button, users can send their feedback to the system. If users want to contribute their resources (time, money, skills, etc.) to the challenge, they can click the "Contribute" button and fill in the appropriate form.

[1409] 6. Management of investment information

[1410] The terminal sends the user's contribution information to the server. The server receives this information and stores it in a database. Once the contribution information is registered, a thank-you message is sent to the user.

[1411] 7. Progress Feedback

[1412] The server periodically updates the progress of the problem-solving process and displays it on a special webpage and application. Users who have invested or sympathized with the project will be notified of the progress by email. A dedicated dashboard will also be provided, allowing users to check detailed progress information in real time.

[1413] Specific examples

[1414] User A inputs and submits "an experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server then sends the received data to a generative model, which verbalizes it specifically as "maternity harassment, a case where a woman is excluded from promotions or work because of pregnancy." The verbalized data is saved in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is saved on the server, and the progress of problem-solving is regularly updated.

[1415] The above is a specific description of an embodiment of the present invention. This system allows for quick verbalization and recognition of issues, and promotes investment and solutions by communities and individuals.

[1416] The processing flow will be explained below.

[1417] Step 1:

[1418] A user logs in to the system's web page or application using a device (smartphone or PC).

[1419] Step 2:

[1420] Users click the "Post a new social issue" button to access a new entry form, where they can enter the social issues or personal suffering they are facing in the text area.

[1421] Step 3:

[1422] When the user completes the input, they press the "Submit" button, which converts the input data into JSON format data on the device.

[1423] Step 4:

[1424] The device sends this JSON format data to the server using the HTTPS protocol, after which a message indicating successful data transmission is displayed to the user.

[1425] Step 5:

[1426] The server analyzes the received JSON data and extracts necessary fields (user ID, details of the social issue, etc.), and prepares the extracted data for passing to the generative model.

[1427] Step 6:

[1428] The server calls the API of the generative model (such as ChatGPT) and sends the analyzed data. Based on the received data, the generative model verbalizes the social issues in appropriate terms.

[1429] Step 7:

[1430] The generative model returns the verbalized data to the server, for example, "Pregnant employees are harassed at work and excluded from promotions and jobs."

[1431] Step 8:

[1432] The server receives the verbalized data and stores it in the database, logging the success of the save.

[1433] Step 9:

[1434] The server then formats the stored data for public viewing and displays it on a special web page or application, making the information accessible to other users.

[1435] Step 10:

[1436] Users can click the "Sympathize" button for a published issue, or if they want to enter a comment or provide specific support, they can click the "Invest" button and enter the required information.

[1437] Step 11:

[1438] The device converts data related to sympathy and investment into JSON format and sends it back to the server via HTTPS protocol.

[1439] Step 12:

[1440] The server receives the empathy data and the contribution data and stores them in a database. Once the contribution information is saved, a thank you message is sent to the user.

[1441] Step 13:

[1442] The server periodically updates the progress of the problem and displays it on a web page or application, allowing users to check the progress.

[1443] Step 14:

[1444] Users can use a dedicated dashboard to check the progress and new information on the projects they have funded in real time.

[1445] Step 15:

[1446] The server periodically notifies the contributor of the progress by email. This notification is sent automatically according to the timing of updates to the progress status within the system.

[1447] This is the specific processing flow of this system, which enables appropriate verbalization and rapid recognition of social issues, as well as promoting investment and solutions by communities and individuals.

[1448] Example 1

[1449] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1450] In conventional systems, it was difficult for users to quickly and appropriately verbalize the personal or social challenges they faced and to solicit sympathy and investment from other users. In addition, there was a lack of visualization of the progress of the challenges and information provided to investors, making it difficult to provide support for problem-solving efficiently.

[1451] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1452] In this invention, the server includes a means for receiving task data entered by a user, a means for converting the task data into JSON format, and a means for transmitting the converted JSON format data via HTTPS, thereby enabling the task data entered by a user to be quickly and appropriately transmitted to the server for analysis and verbalization.

[1453] "User" refers to an individual or corporation that uses this system to input issue data and sympathize with or invest in the project.

[1454] "Issue data" refers to information entered in text format about social issues or personal problems that users are facing.

[1455] "JSON format" is an abbreviation for JavaScript Object Notation, and refers to a lightweight text data format that represents data in a structured manner.

[1456] "HTTPS protocol" stands for HyperText Transfer Protocol Secure and refers to an internet protocol for secure communication.

[1457] A "generative AI model" refers to an artificial intelligence model that uses natural language processing to analyze input data and convert it into an appropriate language.

[1458] A "database" refers to a system for organizing and storing information, and for efficiently searching, retrieving, and updating information as needed.

[1459] "Publication format" refers to a format in which data has been converted into a form that can be viewed by other users, such as HTML or JSON.

[1460] "Empathy" refers to the act of users expressing emotional reactions to published assignment data and sending feedback.

[1461] "Investment" refers to the act of a user providing their own resources (time, money, skills, etc.) to solve a problem.

[1462] A "staging area" refers to an area where received data is temporarily stored and its format and content are validated.

[1463] "Validation" refers to the process of checking whether the content of data is accurate and valid.

[1464] "Dedicated form" refers to a special input screen provided within the system for users to input assignment data.

[1465] The "thank you message" refers to a message sent from the server to the user who made the investment, expressing gratitude.

[1466] A "dashboard" refers to a visual interface that allows users to check the progress of problem-solving in real time.

[1467] A "scheduler" refers to a program that executes a specific process at a fixed time.

[1468] This invention is a system that operates in cooperation with the user, the terminal, and the server. Specifically, it quickly analyzes the problem data entered by the user, properly verbalizes it, and then publishes it, thereby streamlining the process of soliciting sympathy and investment.

[1469] System Configuration

[1470] User Input

[1471] Users access the system using a device (smartphone or PC). They can enter the social issues and personal suffering they are facing in text format through a dedicated web page or application. This input is saved at regular intervals using an auto-save function. After completing the input, the user clicks the send button, and the data is converted into JSON format and sent to the server using the HTTPS protocol.

[1472] Sending and Receiving Data

[1473] The terminal converts the data entered by the user into JSON format and sends it to the server via the HTTPS protocol. The server temporarily stores the received data in a staging area and validates the data to ensure that its format and content are appropriate.

[1474] Data analysis and verbalization

[1475] The server formats the JSON data stored in the staging area so that it can be used by a generative AI model (e.g., ChatGPT). This formatted data is passed to the generative model, which analyzes the data and verbalizes the problem. For example, if an input is "I am being harassed at work because I am pregnant," the generative model verbalizes this as "An example of maternity harassment is being excluded from promotions or work because of pregnancy."

[1476] Storing and publishing verbalized data

[1477] The server stores the verbalized data returned by the generative model in a database. This stored data can then be converted into a publicly available format (e.g., HTML or JSON) and displayed on a dedicated web page or application. This process allows other users to access and view this information.

[1478] Seeking sympathy and investment

[1479] Other users can express their "sympathy" for the published challenge. Users who want to express their sympathy click the "Sympathy" button, and their feedback is sent from their device to the server. Users can also click the "Invest" button and enter details of their resources, such as time, money, or skills, into a dedicated form. This information is also sent from their device to the server.

[1480] Management of investment information

[1481] The terminal converts the user's contribution information into JSON format and sends it to the server via HTTPS. After receiving the contribution information, the server validates it and stores it in the database. After the contribution is completed, a thank-you message is sent to the user.

[1482] Progress feedback

[1483] The server periodically updates the progress of the problem-solving process. This progress information is retrieved from the database and displayed on a dedicated web page or application. Users who have contributed or sympathized with the project are also notified of the progress via email. A system is also provided that allows users to check progress information in real time via a dedicated dashboard.

[1484] Prompt Sentence Examples

[1485] Please explain in detail the harassment you have experienced in the workplace.

[1486] The above is a specific embodiment of the present invention, which enables a user to quickly and appropriately verbalize the issues they face and solicit sympathy and investment from other users.

[1487] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1488] Step 1:

[1489] Users log in to the system using their own device (smartphone or PC). They enter the social issues and personal suffering they are facing in text format into a dedicated form. The input information is automatically saved at regular intervals. Once the input is complete, the user clicks the send button.

[1490] Input: User-entered assignment data (text format)

[1491] Output: Send instructions are generated on the user's terminal

[1492] Step 2:

[1493] The terminal receives the task data entered by the user, converts it into JSON format, and sends the converted data to the server using the HTTPS protocol.

[1494] Input: User-entered assignment data (text format)

[1495] Data processing: Converting issue data into JSON format

[1496] Output: JSON format data is sent to the server

[1497] Step 3:

[1498] The server temporarily stores the JSON data received via HTTPS in a staging area, where the format and content of the data are validated.

[1499] Input: Issue data in JSON format

[1500] Data processing: Validating the format and content of JSON data

[1501] Output: Pass validated JSON data to the generated AI model

[1502] Step 4:

[1503] The server passes the validated JSON data to a generative AI model (e.g., ChatGPT), which analyzes and verbalizes the data. The generative model then organizes the input data into appropriate terms and converts them into specific social issues. For example, if an input states, "I am being harassed at work because I am pregnant," the generative model verbalizes this as, "An example of maternity harassment is being excluded from promotions or jobs at work because of pregnancy."

[1504] Input: Validated JSON data

[1505] Data Computation: Data Analysis and Verbalization with Generative AI Models

[1506] Output: Verbalized task data

[1507] Step 5:

[1508] The server stores the verbalized data returned by the generative AI model in a database, converts the stored data into a publicly available format (e.g., HTML, JSON), and displays it on a dedicated webpage or application.

[1509] Input: Verbalized task data

[1510] Data processing: converting data into a format for publication

[1511] Output: Data displayed on a dedicated web page or application

[1512] Step 6:

[1513] Other users can express their sympathy for the published problem data. By clicking the "Sympathize" button, feedback is sent from the device to the server. Users can also click the "Invest" button and enter details of their resources, such as time, money, or skills, into a dedicated form. This information is also sent from the device to the server.

[1514] Input: The like or pledge button the user clicked

[1515] Data processing: Sending feedback or contribution information

[1516] Output: Empathy or pledge data sent to the server

[1517] Step 7:

[1518] The server receives the sympathy and contribution data, validates the contents, and stores them in the database. After the contribution is completed, a thank you message is sent to the user.

[1519] Input: Empathy data, investment data

[1520] Data processing: validation and saving to database

[1521] Output: Validated empathy data, pledge data, and a thank you message

[1522] Step 8:

[1523] The server periodically updates the progress of the project. This progress information is retrieved from the database and displayed on a dedicated web page or application. Users who have contributed or sympathized are notified of the progress by email, and can check the progress information in real time through a dedicated dashboard.

[1524] Input: Progress information in the database

[1525] Data processing: Updating and obtaining progress information

[1526] Output: Publishing and notifying progress updates

[1527] (Application example 1)

[1528] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1529] Conventional problem-solving systems lacked sufficient means for users to quickly verbalize the social issues and personal suffering they faced and then share that information widely. Furthermore, they lacked a means to create advertisements based on verbalized problem data and efficiently solicit sympathy and investment, making it difficult to effectively gather support for problem-solving. For this reason, a new system was needed to quickly and effectively solve users' problems across society.

[1530] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1531] In this invention, the server includes means for transmitting problem data entered by the user to a generative model for analysis and verbalization, means for embedding the generated verbalized data in an advertising template to generate an advertisement, and means for distributing the generated advertisement to social media and websites. This makes it possible to quickly share users' problems and generate advertisements based on them to effectively attract sympathy and investment.

[1532] A "user" is an individual or organization that inputs assignment data and shares that assignment through the system.

[1533] "Issue data" is text data that expresses the social issues and personal suffering that users are facing.

[1534] A "generative model" is an artificial intelligence model that analyzes input task data and converts it into appropriate words.

[1535] "Verbalized data" is task data that has been analyzed by a generative model and converted into an appropriate format.

[1536] An "advertising template" is a model of an advertisement prepared for embedding generated verbalized data.

[1537] "Advertising" refers to content generated based on verbalized data and distributed on social media and websites.

[1538] "Social media" is a general term for online platforms through which users receive advertising.

[1539] A "Website" is an online page for displaying advertisements on the Internet.

[1540] "Empathy" is an act in which other users show emotional understanding and support for a published issue.

[1541] "Contribution" is the act of a user providing resources such as time, money, or skills to a published challenge.

[1542] "Progress information" is data that indicates the progress of problem solving and the current situation.

[1543] "Advertising status management" is the process of monitoring and controlling the status of advertising on social media and websites.

[1544] This invention is a system that allows users to quickly verbalize social issues and personal suffering they are facing and share it widely. This system aims to effectively attract sympathy and investment by creating advertisements based on the generated verbalization data through collaboration between users, devices, generative models, and servers.

[1545] System Overview

[1546] 1. User input:

[1547] Users access the system using devices such as smartphones or PCs. A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. The text entered in this form is treated as assignment data.

[1548] 2. Receiving and sending assignment data:

[1549] The terminal receives the assignment data entered by the user, converts it into JSON format, and then sends the converted data to the server using the HTTPS protocol.

[1550] 3. Data analysis and verbalization:

[1551] The server passes the received JSON data to a generative model (such as ChatGPT) to analyze and verbalize the data. The generative model then organizes and converts the problem data into appropriate language, converting it into specific social issues.

[1552] 4. Ad generation and delivery:

[1553] The server embeds the generated verbalized data into an advertising template, which generates an advertisement designed to resonate with users. The generated advertisement is then distributed to social media and websites. The server also collects and analyzes user feedback on the advertisement to evaluate its effectiveness.

[1554] 5. Empathy and stake management:

[1555] Other users can express their sympathy for the published issues. Data on sympathy and contributions is also sent to the server and stored in a database. The server periodically updates the progress of the issue and notifies the contributors and other stakeholders by email.

[1556] Specific examples

[1557] For example, User A inputs her experience of "being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server then sends this data to a generative model, which verbalizes it specifically as "problems related to maternity harassment in the workplace." The verbalized data is embedded in an ad template, and an ad is automatically generated that reads, "(Relatable ad) Problem: Maternity harassment is occurring in the workplace. We need your support. Learn more: www.example.com / donate." This ad is then distributed on social media and websites, and feedback is collected.

[1558] Prompt Sentence Examples

[1559] An example of an input prompt for a generative AI model is as follows:

[1560] "Verbalize the following user input for advertising: I am being harassed at work because I am pregnant"

[1561] The above description provides a detailed explanation of how the present invention can be implemented, allowing users to quickly articulate the challenges they face and gain widespread sympathy and investment.

[1562] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1563] Step 1:

[1564] Users access a dedicated web page or application using a device such as a smartphone or PC and input their experiences and thoughts. The input data is treated as assignment data. In this case, the text data entered by the user becomes input data to be passed on to the next processing step.

[1565] Step 2:

[1566] The terminal receives the assignment data entered by the user and converts it into JSON format. The converted data is sent to the server using the HTTPS protocol. Here, the input is the assignment data and the output is JSON format data.

[1567] Step 3:

[1568] The server passes the received JSON data to a generative model, which analyzes and verbalizes the data. The generative model (such as ChatGPT) organizes and converts the task data into appropriate language. The input for this process is JSON data, and the output is verbalized data. Specific data processing involves analyzing the task data and converting it into appropriate language expressions.

[1569] Step 4:

[1570] The server embeds the generated verbalized data into an advertising template. The advertising template is a pre-prepared format, and specific advertising content is generated by embedding the verbalized data. The inputs to this process are the verbalized data and the advertising template, and the output is the generated advertisement. Specifically, the verbalized data is inserted into a placeholder in the template.

[1571] Step 5:

[1572] The server distributes the generated advertisements to social media platforms and websites. After the advertisements are distributed, users can provide feedback on the advertisements. The input of this process is the generated advertisement, and the output is the distributed advertisement and user feedback. Specifically, the advertisements are sent to social media APIs and the website's advertisement management system.

[1573] Step 6:

[1574] The server collects and analyzes user responses to advertisements from social media and websites. The effectiveness of the advertisements is evaluated based on the collected feedback data. The input to this process is the feedback data, and the output is the analysis results. Specifically, the feedback data is stored in a database and statistical analysis and text mining are performed.

[1575] Step 7:

[1576] Other users can express their support or investment in the published issues. The server also receives this data and stores it in a database. Based on the support and investment data, progress information on the issue resolution is generated, updated periodically, and notified to investors and related parties via email. The input to this process is support and investment data, and the output is progress information and notification emails. Specifically, the support and investment data is analyzed, progress information is generated, and notifications are sent using the email system.

[1577] The above are the specific processing steps of the system program that realizes the application example.

[1578] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1579] This invention is a system that aims to quickly verbalize the social issues and personal suffering faced by users, and to widely solicit sympathy and investment. This system is based on collaboration between a server, a device, and a user, and is characterized by its ability to appropriately verbalize issues using a generative model. In addition, by combining it with an emotion engine that recognizes the user's emotions, it enables more accurate analysis and more effective motivation for sympathy and investment.

[1580] System Overview

[1581] 1. User Input

[1582] Users access the system using a device (smartphone or PC). A dedicated web page or application provides a form where users can freely enter their experiences and thoughts. Here, users enter text about the social issues and personal suffering they are facing. Once they have finished entering the text, they press the send button.

[1583] 2. Sending and Receiving Input Data

[1584] The terminal receives the data entered by the user, converts it to JSON format, and then sends the converted data using the HTTPS protocol to the server, which receives the data and prepares it for analysis.

[1585] 3. Emotion Data Recognition and Analysis

[1586] The server applies an emotion engine to the received JSON data to analyze the user's emotions. For example, it extracts emotions (happiness, sadness, anger, etc.) from the text data and generates an emotion score.

[1587] 4. Data analysis and verbalization

[1588] Taking the analyzed emotion data into consideration, the server passes the received JSON data to a generative model (such as ChatGPT) for data analysis and verbalization. The generative model then organizes the problem data into appropriate terms and converts it into a specific social issue. For example, a statement such as "A pregnant employee was harassed at work and excluded from promotions and work" can be verbalized as "An example of maternity harassment is being excluded from promotions and work due to pregnancy."

[1589] 5. Preservation and publication of verbalized data

[1590] The server stores the verbalized and emotional data returned by the generative model in a database, which then converts the data into a publicly available format and displays it on a dedicated web page or application, allowing other users to access and view the information.

[1591] 6. Seeking sympathy and investment

[1592] Other users can sympathize with the published challenge. By clicking the "Sympathize" button, users can send their feedback to the system. If users want to contribute their resources (time, money, skills, etc.) to the challenge, they can click the "Contribute" button and fill in the appropriate form.

[1593] 7. Management of investment information

[1594] The terminal sends the user's contribution information to the server. The server receives this information and stores it in a database. Once the contribution information is registered, a thank-you message is sent to the user.

[1595] 8. Progress Feedback

[1596] The server periodically updates the progress of the problem-solving process and displays it on a special webpage and application. Users who have invested or sympathized with the project will be notified of the progress by email. A dedicated dashboard will also be provided, allowing users to check detailed progress information in real time.

[1597] Specific examples

[1598] User A inputs and submits her "experience of workplace harassment due to pregnancy." This data is converted to JSON format and sent to the server via HTTPS protocol. The server analyzes the received data through an emotion engine and generates an emotion score. This is then sent to the generative model along with the analyzed emotion data, which is then specifically verbalized as "maternity harassment, a case where a woman is excluded from promotions or work due to pregnancy." The verbalized data and emotion data are stored in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is stored on the server, and the progress of problem-solving is regularly updated.

[1599] The above is a specific description of an embodiment of the present invention. This system enables quick verbalization and recognition of issues, and promotes investment and solutions by communities and individuals. Furthermore, by recognizing the user's emotions, it is possible to empathize more effectively and motivate investment.

[1600] The processing flow will be explained below.

[1601] Step 1:

[1602] A user logs in to the system's web page or application using a device (smartphone or PC).

[1603] Step 2:

[1604] The user clicks the "Post a new social issue" button to access a new entry form. Here, the user enters the social issue or personal suffering they are facing into the text area. For example, the user could provide details such as "I was harassed at work because I am pregnant."

[1605] Step 3:

[1606] When the user completes the input, they press the "Submit" button, which converts the input data into JSON format data on the device.

[1607] Step 4:

[1608] The device sends this JSON format data to the server using the HTTPS protocol, after which a message indicating successful data transmission is displayed to the user.

[1609] Step 5:

[1610] The server analyzes the received JSON data and extracts necessary fields (user ID, details of the social issue, etc.), and prepares the extracted data for passing to the generative model.

[1611] Step 6:

[1612] The server sends the task data to the emotion engine, which extracts emotions from the text data and generates an emotion score (e.g., a range from 0 to 1 representing joy, sadness, anger, etc.).

[1613] Step 7:

[1614] The analyzed data, along with the emotion score generated by the server, is sent to a generative model (e.g., ChatGPT) for analysis and verbalization. The generative model then organizes the issue data into concrete terms and converts it into a social issue. For example, "I was harassed at work because I was pregnant" is verbalized as "An example of maternity harassment is when a woman is excluded from promotions or jobs at work because she is pregnant."

[1615] Step 8:

[1616] The server saves the verbalized data and sentiment scores returned by the generative model to a database, and logs the success of the save.

[1617] Step 9:

[1618] The server then formats the stored data for public viewing and displays it on a special web page or application, making the information accessible to other users.

[1619] Step 10:

[1620] Users can click the "Sympathize" button for a published issue, or if they want to enter a comment or provide specific support, they can click the "Invest" button and enter the required information.

[1621] Step 11:

[1622] The device converts data related to sympathy and investment into JSON format and sends it back to the server via HTTPS protocol.

[1623] Step 12:

[1624] The server receives the empathy data and the contribution data and stores them in a database. Once the contribution information is saved, a thank you message is sent to the user.

[1625] Step 13:

[1626] The server periodically updates the progress of the problem and displays it on a web page or application, allowing users to check the progress.

[1627] Step 14:

[1628] Users can use a dedicated dashboard to check the progress and new information on the projects they have funded in real time.

[1629] Step 15:

[1630] The server periodically notifies the contributor of the progress by email. This notification is sent automatically according to the timing of updates to the progress status within the system.

[1631] As a concrete example, User A inputs and submits "an experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server analyzes the received data using an emotion engine to generate an emotion score. This is then sent to the generative model along with the analyzed emotion data, which is specifically verbalized as "maternity harassment, a case where a woman is excluded from promotions or work because of pregnancy." The verbalized data and emotion data are stored in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and makes an additional investment of 1,000 yen. This information is stored on the server, and the progress of problem-solving is regularly updated.

[1632] The above is the specific processing flow of this system. This enables appropriate verbalization and rapid recognition of social issues, as well as promoting investment and solutions by communities and individuals. Furthermore, the introduction of an emotion engine enables analysis that takes into account the user's emotions and expands empathy.

[1633] Example 2

[1634] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1635] In modern society, there is a lack of ways for individuals to quickly verbalize the social issues and personal suffering they face and to solicit widespread sympathy and investment. As a result, individual problems are not easily recognized by society, and it takes a long time to receive effective support. Furthermore, the lack of a system that can appropriately handle users' emotions means that there is insufficient motivation for empathy and investment.

[1636] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1637] In this invention, the server includes means for receiving task data entered by a user, means for converting the received task data into JSON format, means for transmitting the converted data via HTTPS, means for analyzing the task data and generating an emotional score, means for transmitting the analyzed emotional score and task data to a generative AI model for analysis and verbalization, means for saving the verbalized task data in a database, means for generating and publishing the saved task data for display, means for accepting sympathy and contributions for the published task data, means for receiving and saving the sympathy and contribution data, and means for generating, publishing, and notifying progress information on problem solving. This enables rapid verbalization and widespread sharing of task data and motivates sympathy and contributions.

[1638] "User" refers to any individual or entity that uses the System.

[1639] "Issue data" refers to text data entered by users about social issues or personal suffering.

[1640] "JSON format" refers to a JavaScript Object Notation data structure, a text format used for exchanging and storing data.

[1641] The "HTTPS protocol" is a communication protocol for securely transferring data over the Internet.

[1642] "Emotion score" refers to a numerical representation of the type and intensity of emotions extracted from text data.

[1643] A "generative AI model" refers to an artificial intelligence algorithm that uses a large-scale language model to parse and verbalize data.

[1644] A "database" refers to a system for efficiently storing, managing, and searching large amounts of data.

[1645] "Publication" refers to making the stored data publicly available for viewing via the Internet.

[1646] "Empathy" refers to the act of other users showing sympathy or understanding for a published issue.

[1647] "Contribution" refers to the act of other users providing resources (funds, time, skills, etc.) to a published challenge.

[1648] "Thank you message" refers to a message of gratitude sent from the server when a user makes a contribution.

[1649] "Progress information" refers to data regarding the progress of activities toward resolving a problem.

[1650] A "dashboard" refers to an interface designed to allow users to see the status and progress of a system at a glance.

[1651] This invention is a system that aims to quickly verbalize the social issues and personal suffering faced by users, and to widely solicit sympathy and investment. The system is based on three-way collaboration between a server, a terminal, and a user. This enables the appropriate verbalization of issues using a generative AI model, combined with an emotion engine that recognizes the user's emotions, enabling more accurate analysis and effective motivation for sympathy and investment. The specific hardware and software used will be explained in turn.

[1652] First, the user accesses the system using a terminal. The terminal can be a smartphone or personal computer, and a form is provided for the user to enter their experiences and thoughts. The user enters the assignment data through a dedicated web page or application and presses the submit button.

[1653] The device receives the text data entered by the user and converts it into JSON format. It then sends it to the server using the HTTPS protocol. The server prepares the received JSON data for analysis. Specifically, the server uses an emotion engine (e.g., IBM Watson or Google Cloud Natural Language API) to analyze the user's emotions. This process extracts emotions such as joy, sadness, and anger from the entered text data and generates an emotion score.

[1654] The server then passes the analyzed emotion data and issue data to a generative AI model (such as ChatGPT). The generative AI model then organizes the given issue data into appropriate language and converts it into a specific social issue. For example, a statement such as "A pregnant employee was harassed at work and excluded from promotions and work" can be verbalized as "Maternity harassment involves being excluded from promotions and work due to pregnancy."

[1655] The server stores the verbalized data in a database, converts the data into a public format, and instantly publishes it on a special web page or application, allowing other users to view the information.

[1656] Other users can show their support or investment in the published challenge. By clicking the "Support" button, users can send feedback to the system. Also, by clicking the "Invest" button, users who want to donate their resources (time, money, skills, etc.) can fill out the appropriate form and send it from their device to the server. The server stores the received investment information in a database and manages it.

[1657] Furthermore, the server periodically updates the progress of the project and displays it on a special webpage or application. Users who sympathize or invest in the project will be notified of the progress by email. Users can check detailed progress information in real time via a dedicated dashboard.

[1658] Examples:

[1659] User A inputs and submits her "experience of being harassed at work because of pregnancy." This data is converted into JSON format and sent to the server via HTTPS protocol. The server analyzes the received data using an emotion engine to generate an emotion score. This is then sent to a generative model along with the analyzed emotion data, which is then specifically verbalized as "maternity harassment, being excluded from promotions or work because of pregnancy." The verbalized data and emotion data are saved in a database and immediately published on a special webpage. User B reads the article, expresses sympathy, and contributes an additional 1,000 yen. This information is saved on the server, and progress in solving the problem is regularly updated.

[1660] Example prompt sentence:

[1661] "I feel that I have been harassed at work because I am pregnant. Based on this experience, please appropriately articulate what kind of social issue this is."

[1662] The above is a specific embodiment of the present invention. A system is constructed that recognizes the user's emotions at each processing step and provides appropriate empathy and motivation for investment.

[1663] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1664] Step 1:

[1665] User Input

[1666] Users access the system using a device (smartphone or PC). They enter text about the social issues they face or their personal suffering into an input form on a dedicated webpage or application, and click the submit button. For example, a user might enter "My experience of being harassed at work because of my pregnancy." The input data is sent to the device in text format.

[1667] Input: Text data entered by the user

[1668] Output: Text data is saved to the device.

[1669] Step 2:

[1670] Sending and Receiving Input Data

[1671] The terminal converts the text data entered by the user into JSON format using a JSON encoder running on the terminal, and then sends the converted data to the server using the HTTPS protocol. The server checks the integrity of the received JSON data and prepares it for parsing.

[1672] Input: Text data

[1673] Output: JSON format data

[1674] Specific behavior:

[1675] The device encodes the text data into JSON format.

[1676] The converted JSON data is sent to the server via HTTPS protocol.

[1677] The server verifies the integrity of the data received.

[1678] Step 3:

[1679] Emotional Data Recognition and Analysis

[1680] The server passes the received JSON data to an emotion engine (e.g., IBM Watson or Google Cloud Natural Language API) to analyze the user's emotions. This analysis process extracts emotions (happiness, sadness, anger, etc.) from the text data and generates an emotion score. The server receives the generated emotion score and prepares it for the next step.

[1681] Input: JSON format data

[1682] Output: Sentiment score

[1683] Specific behavior:

[1684] The server passes the JSON data to the emotion engine.

[1685] The emotion engine extracts emotions from the text data and generates an emotion score.

[1686] A server receives the emotion scores from the emotion engine.

[1687] Step 4:

[1688] Data analysis and verbalization

[1689] The server passes the emotion score and analyzed JSON data to a generative AI model (e.g., ChatGPT). The generative AI model then organizes the input issue data into appropriate terms and converts them into specific social issues. For example, "experiences of workplace harassment due to pregnancy" can be verbalized as "maternity harassment, being excluded from promotions or work due to pregnancy."

[1690] Input: sentiment scores, parsed JSON data

[1691] Output: Verbalized text data

[1692] Specific behavior:

[1693] The server sends the sentiment scores and parsed JSON data to the generative AI model.

[1694] The generative AI model organizes the information into appropriate words and verbalizes it as a specific social issue.

[1695] The server receives the verbalized data.

[1696] Step 5:

[1697] Storing and publishing verbalized data

[1698] The server stores the verbalized text data returned by the generative model in a database, converts it into a publicly available format, and displays it on a dedicated web page or application, allowing other users to access and view the information.

[1699] Input: Verbalized text data

[1700] Output: Public data displayed on a dedicated web page or application

[1701] Specific behavior:

[1702] The server stores the verbalized data in a database.

[1703] Convert the stored data into a publishing format (e.g. HTML, JSON).

[1704] The published data will be displayed on special web pages and applications.

[1705] Step 6:

[1706] Seeking sympathy and investment

[1707] Other users can show their support or contribution to the published issue. Users click the "Support" button to send feedback, or click the "Contribute" button to fill out a form and send it to the server from their device. The server processes the received support and contribution data.

[1708] Input: User sympathy and investment information

[1709] Output: Sympathy and pledge data stored on the server

[1710] Specific behavior:

[1711] A user views the public data and clicks the sympathy or contribution button.

[1712] Enter your sympathy and investment information and send it from your device to the server.

[1713] The server stores the received data in a database.

[1714] Step 7:

[1715] Management of investment information

[1716] The terminal sends the contribution information entered by the user to the server. The server receives this information and stores it in a database. After confirming that the contribution information has been successfully saved, a thank-you message is sent to the user.

[1717] Input: Investment information

[1718] Output: Contribution information stored in the database, a thank you message

[1719] Specific behavior:

[1720] The terminal transmits the user's contribution information to the server.

[1721] The server stores the investment information in a database.

[1722] Send a thank you message to the user.

[1723] Step 8:

[1724] Progress feedback

[1725] The server periodically updates the progress of the project and displays it on a special webpage and application. Users who sympathize with or invest in the project are notified of the progress by email. Users can also check detailed progress information in real time via a dedicated dashboard.

[1726] Input: Progress information

[1727] Output: Progress information displayed on a dedicated web page or in the application, notification emails sent to users

[1728] Specific behavior:

[1729] The server updates the progress of the issue resolution.

[1730] Display it on a special web page or application.

[1731] Users who have sympathized or invested will be notified of progress via email.

[1732] Users can view progress information on a dedicated dashboard.

[1733] (Application example 2)

[1734] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1735] Previous systems lacked the means to quickly and appropriately verbalize the social challenges and personal suffering they faced and share those experiences with other users. Furthermore, the lack of specific methods for soliciting sympathy and investment, and the lack of clear feedback on progress, weakened users' motivation to solve the problems. Furthermore, the lack of a mechanism for properly recognizing users' emotions made effective analysis difficult.

[1736] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving task data entered by a user, means for transmitting the task data to a generative model and analyzing and verbalizing it, means for saving the verbalized task data in a database, means for generating and publishing the saved task data for display, means for accepting sympathy and contributions for the published task data, means for receiving and saving the sympathy and contribution data, means for generating, publishing, and notifying task-solving progress information, means for receiving task data entered by a user from a smartphone application, and means for generating emotion data by applying the generated data to an emotion analysis engine. This allows the task data entered by a user to be quickly and appropriately verbalized and shared with many users, making it easier to solicit sympathy and contributions and enabling timely feedback on the progress of task solving.

[1737] "User-entered problem data" is text information that describes the social problems and personal difficulties that the user is facing.

[1738] A "generative model" is a model that uses artificial intelligence to analyze input data and appropriately verbalize it in natural language.

[1739] An "emotion analysis engine" is software that analyzes a user's emotions from input text and generates emotional data.

[1740] The "database" is a data storage system for storing and managing verbalized issue data and empathy / investment data.

[1741] "Sympathy and investment" refers to the act of a user emotionally supporting a published issue and providing funds or resources.

[1742] "Progress information" is data that indicates the current status and progress of efforts to solve a problem.

[1743] A "web page" is a page for displaying information that is published on the Internet and can be viewed by users.

[1744] A "dashboard" is an interface that allows users to visually check their progress.

[1745] A "smartphone application" is a software application that runs on a smartphone and is a means by which a user inputs and transmits assignment data.

[1746] The "HTTPS protocol" is an internet protocol for securely transmitting data.

[1747] This invention is a system that allows users to quickly verbalize the social issues and personal suffering they are facing, and solicit sympathy and investment from other users. This system is realized through cooperation between a server, a terminal, and a user.

[1748] 1. User Input

[1749] Users access the system using a smartphone application and input their own problem data, which may include social issues or personal difficulties, such as experiencing harassment at work because of pregnancy. The input data is then sent from the smartphone application to the server.

[1750] 2. Sending and Receiving Data

[1751] The terminal converts the task data entered by the user into JSON format and sends it to the server using the HTTPS protocol. The server prepares the received task data for analysis.

[1752] 3. Emotion analysis and verbalization

[1753] The server runs the received task data through an emotion analysis engine to analyze the user's emotions. For example, emotions such as sadness or anger are extracted from the text and emotion data is generated. The emotion-analyzed data and task data are then sent to a generative AI model, which then translates the data into appropriate language.

[1754] 4. Preservation and publication of verbalized data

[1755] The server stores the verbalized data returned by the generative AI model in a database, which then publishes the data in real time on a special webpage.

[1756] 5. Accepting sympathy and investment

[1757] Other users can express their sympathy for the issue data published on the web page. If they want to donate resources such as time, money, or skills, they can click the contribution button and fill in the appropriate form. This sympathy and contribution data is received by the server and stored in a database.

[1758] 6. Progress Feedback

[1759] The server will periodically update the progress of the project and make it available to users via a special webpage and a dedicated dashboard. Users who have contributed will also be notified of the progress via email.

[1760] Hardware and software used

[1761] Hardware: Smartphone, Server (e.g. AWS, GCP)

[1762] Software: Python, Hugging Face Transformers, OpenAI GPT-3

[1763] At each step of this system, the user's input data is analyzed and verbalized appropriately through a sentiment analysis engine and a generative AI model, and then published in real time, enabling other users to sympathize with and contribute. As a concrete example, let's use the following prompt sentence.

[1764] Prompt Sentence Examples

[1765] Social Issue: Harassment at Work Because of Pregnancy

[1766] Emotion: [{'label': 'Sad', 'score': 0.95}]

[1767] To put this in words:

[1768] This allows the problem data entered by users to be quickly and appropriately verbalized and shared with many users.The system promotes awareness of problems and functions as a platform for soliciting sympathy and investment to create more effective solutions.

[1769] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1770] Step 1:

[1771] The user starts the smartphone application and inputs their assignment data. For example, the user may enter text about their experience of being harassed at work because of pregnancy. This input data is temporarily saved by the smartphone application.

[1772] input:

[1773] Assignment text (e.g., "I was harassed at work because I was pregnant.")

[1774] output:

[1775] Temporarily saved text data

[1776] Step 2:

[1777] The terminal converts the saved text data into JSON format and sends it to the server using the HTTPS protocol. The converted JSON data contains the text content.

[1778] input:

[1779] Temporarily saved text data

[1780] Data processing:

[1781] Convert text data to JSON format

[1782] output:

[1783] Issue data in JSON format

[1784] Step 3:

[1785] The server receives the assignment data in JSON format sent from the device, and temporarily stores the received data in preparation for analysis.

[1786] input:

[1787] Issue data in JSON format

[1788] output:

[1789] Temporarily saved JSON format issue data

[1790] Step 4:

[1791] The server runs the received task data through a sentiment analysis engine to analyze the user's emotions. The sentiment analysis engine extracts emotions (happiness, sadness, anger, etc.) from the text and generates an emotion score. For example, the emotion "sad" and its score are extracted.

[1792] input:

[1793] Issue data in JSON format

[1794] Data Calculation:

[1795] Sentiment extraction and scoring through text analysis

[1796] output:

[1797] Emotion data (e.g., sad 0.95)

[1798] Step 5:

[1799] The server sends the analyzed emotion data and issue data to the generative AI model, which then verbalizes them appropriately. The generative AI model then organizes the issue data and verbalizes it as a specific social issue. For example, "an experience of being harassed at work because of pregnancy" is verbalized as "an example of maternity harassment is being excluded from promotions or work because of pregnancy."

[1800] input:

[1801] Emotion data and issue data

[1802] Data Calculation:

[1803] Verbalization using generative AI models

[1804] output:

[1805] Verbalized problem data

[1806] Step 6:

[1807] The server stores the verbalized assignment data in a database, after which the assignment data is made public in real time on a special web page.

[1808] input:

[1809] Verbalized problem data

[1810] output:

[1811] Data stored in the database, published assignment data

[1812] Step 7:

[1813] Users can view the issue data published on the webpage and sympathize or contribute. To sympathize, click the "Sympathize" button, and to contribute, click the "Contribute" button and enter the necessary information in the appropriate form. This generates sympathy and contribution data.

[1814] input:

[1815] Published assignment data

[1816] output:

[1817] Empathy or sponsorship data

[1818] Step 8:

[1819] The server receives the empathy and contribution data and stores it in a database. After storing it, the progress of the problem solving is updated and notified to the user.

[1820] input:

[1821] Empathy and investment data

[1822] output:

[1823] Sympathy and investment data stored in database, progress notifications

[1824] Step 9:

[1825] The server will periodically update the progress of the project and make it available to users via a special webpage and a dedicated dashboard. Users who have contributed will also be notified of the progress via email.

[1826] input:

[1827] Progress Information

[1828] output:

[1829] Progress updates, notification emails

[1830] The above are the specific processing steps of the system that realizes the application example.

[1831] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1832] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1833] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1834] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1835] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1836] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1837] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1838] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1839] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1840] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1841] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1842] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1843] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1844] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1845] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1846] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1847] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1848] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1849] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1850] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1851] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1852] The following is further disclosed regarding the above embodiment.

[1853] (Claim 1)

[1854] means for receiving user-entered assignment data;

[1855] A means for transmitting the problem data to a generative model and analyzing and verbalizing the problem data;

[1856] A means for storing verbalized task data in a database;

[1857] a means for generating and publishing the saved issue data for display;

[1858] A means of receiving sympathy and contributions for the published problem data;

[1859] means for receiving and storing said sympathy and contribution data;

[1860] A means for generating, publishing and notifying progress information on the resolution of issues;

[1861] A system including:

[1862] (Claim 2)

[1863] A means to convert user-entered issue data into JSON format,

[1864] means for transmitting the data converted into JSON format via HTTPS protocol;

[1865] A means of converting the verbalized data returned by the generative model into an appropriate format; and

[1866] The system of claim 1 further comprising:

[1867] (Claim 3)

[1868] A method to regularly update the progress of the problem and notify the investors by email,

[1869] A way for users to check their progress using a dedicated dashboard;

[1870] The system of claim 1 further comprising:

[1871] "Example 1"

[1872] (Claim 1)

[1873] means for receiving user-entered assignment data;

[1874] means for converting the assignment data into a JSON format;

[1875] A means of transmitting the converted JSON format data via HTTPS protocol;

[1876] A means for transmitting the problem data to a generative AI model, and for analyzing and verbalizing the problem data;

[1877] A means for storing verbalized task data in a database;

[1878] a means for generating and publishing the saved issue data for display;

[1879] A means of receiving sympathy and contributions for the published problem data;

[1880] means for receiving and storing said sympathy and contribution data;

[1881] A means for generating, publishing and notifying progress information on the resolution of issues;

[1882] A system including:

[1883] (Claim 2)

[1884] 10. The system of claim 1, further comprising means for converting the verbalized data returned by the generative AI model into an appropriate format.

[1885] (Claim 3)

[1886] A method to regularly update the progress of the problem and notify the investors by email,

[1887] A way for users to check their progress using a dedicated dashboard;

[1888] The system of claim 1 further comprising:

[1889] "Application Example 1"

[1890] (Claim 1)

[1891] means for receiving user-entered assignment data;

[1892] A means for transmitting the problem data to a generative model and analyzing and verbalizing the problem data;

[1893] A means for storing verbalized task data in a database;

[1894] a means for generating and publishing the saved issue data for display;

[1895] A means of receiving sympathy and contributions for the published problem data;

[1896] means for receiving and storing said sympathy and contribution data;

[1897] A means for generating, publishing and notifying progress information on the resolution of issues;

[1898] A means for embedding the generated verbalized data into an advertisement template to generate an advertisement;

[1899] means for distributing the generated advertisements to social media and websites;

[1900] means for collecting and analyzing user responses to advertisements;

[1901] A system including:

[1902] (Claim 2)

[1903] A means to convert user-entered issue data into JSON format,

[1904] means for transmitting the data converted into JSON format via HTTPS protocol;

[1905] A means of converting the verbalized data returned by the generative model into an appropriate format; and

[1906] means for collecting and analyzing feedback data of the generated advertisements;

[1907] The system of claim 1 further comprising:

[1908] (Claim 3)

[1909] A method to regularly update the progress of the problem and notify the investors by email,

[1910] A way for users to check their progress using a dedicated dashboard;

[1911] A means to manage the distribution of advertisements on social media and websites;

[1912] The system of claim 1 further comprising:

[1913] "Example 2: Combining Emotion Engines"

[1914] (Claim 1)

[1915] means for receiving user-entered assignment data;

[1916] A means to convert received issue data into JSON format,

[1917] A means for transmitting the converted data via HTTPS protocol;

[1918] means for analyzing the task data and generating an emotion score;

[1919] A means for transmitting the analyzed emotion scores and task data to a generative AI model for analysis and verbalization;

[1920] A means for storing verbalized task data in a database;

[1921] a means for generating and publishing the saved issue data for display;

[1922] A means of receiving sympathy and contributions for the published problem data;

[1923] means for receiving and storing said sympathy and contribution data;

[1924] A means for generating, publishing and notifying progress information on the resolution of issues;

[1925] A system including:

[1926] (Claim 2)

[1927] A means for analyzing the converted JSON format data using an emotion engine to generate an emotion score;

[1928] A means of converting the verbalized data returned by the generative model into an appropriate format; and

[1929] The system of claim 1 further comprising:

[1930] (Claim 3)

[1931] A method to regularly update the progress of the problem and notify the investors by email,

[1932] A way for users to check their progress using a dedicated dashboard;

[1933] The system of claim 1 further comprising:

[1934] "Application example 2 when combining emotion engines"

[1935] (Claim 1)

[1936] means for receiving user-entered assignment data;

[1937] A means for transmitting the problem data to a generative model and analyzing and verbalizing the problem data;

[1938] A means for storing verbalized task data in a database;

[1939] a means for generating and publishing the saved issue data for display;

[1940] A means of receiving sympathy and contributions for the published problem data;

[1941] means for receiving and storing said sympathy and contribution data;

[1942] A means for generating, publishing and notifying progress information on the resolution of issues;

[1943] A means for receiving assignment data entered by a user from a smartphone application;

[1944] means for subjecting the generated data to an emotion analysis engine to generate emotion data;

[1945] A system including:

[1946] (Claim 2)

[1947] A means to convert user-entered issue data into JSON format,

[1948] means for transmitting the data converted into JSON format via HTTPS protocol;

[1949] A means of converting the verbalized data returned by the generative model into an appropriate format; and

[1950] A means for publishing the emotion-analyzed data and the data verbalized by the generative model on a special webpage in real time;

[1951] The system of claim 1 further comprising:

[1952] (Claim 3)

[1953] A method to regularly update the progress of the problem and notify the investors by email,

[1954] A way for users to check their progress using a dedicated dashboard;

[1955] A means of notifying users of their sympathy and investment status,

[1956] The system of claim 1 further comprising: [Explanation of symbols]

[1957] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving user-entered assignment data; A means for transmitting the problem data to a generative model and analyzing and verbalizing the problem data; A means for storing verbalized task data in a database; a means for generating and publishing the saved issue data for display; A means of receiving sympathy and contributions for the published problem data; means for receiving and storing said sympathy and contribution data; A means for generating, publishing and notifying progress information on the resolution of issues; A system including:

2. A means to convert user-entered issue data into JSON format, means for transmitting the data converted into JSON format via HTTPS protocol; A means of converting the verbalized data returned by the generative model into an appropriate format; and The system of claim 1 further comprising:

3. A method to regularly update the progress of the problem and notify the investors by email, A way for users to check their progress using a dedicated dashboard; The system of claim 1 further comprising:

Images